NIPS2023论文集

oral

Additive Decoders for Latent Variables Identification and CartesianProduct Extrapolation
Are Emergent Abilities of Large Language Models a Mirage
Augmenting Frozen Language Models with Massive Tools via Tool Embeddings
A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
A MeasureTheoretic Axiomatisation of Causality
A Probabilistic Programming Approach
A Rigorous Link between Deep Ensembles and Variational Bayesian Methods
A Simple SubQuadratic GEMMBased Architecture
A SingleLoop Accelerated ExtraGradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization
A Theoretical Perspective
Breeding Soft Robots With PhysicsAugmented Generative Diffusion Models
Bridging RL Theory and Practice with the Effective Horizon
Characteristic Circuits
Clifford Group Equivariant Neural Networks
Conformal Metalearners for Predictive Inference of Individual Treatment Effects
conservation laws for gradient flows
Cortical Discovery using Large Scale Generative Models
Deliberate Problem Solving with Large Language Models
Efficient Finetuning of Quantized LLMs
Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity
Enhancing Attribute Correspondence through Attention Map Alignment
Entropic Neural Optimal Transport via Diffusion Processes
Evaluating Posthoc Explanations for Graph Neural Networks via Robustness Analysis
Fairer Architectures Make for Fairer Face Recognition
FineTuning Language Models with Just Forward Passes
from theory to practice
Generalizing Nonlinear ICA Beyond Structural Sparsity
Going beyond persistent homology using persistent homology
Highquality Video Reconstruction from Brain Activity
How Does LLM Safety Training Fail
How to Turn Your Knowledge Graph Embeddings into Generative Models
Humancentric environment representations from egocentric video
Humanlike FewShot Learning via Bayesian Reasoning over Natural Language
Image Captioners Are Scalable Vision Learners Too
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures
Improved Editing of PreTrained Models
Language Models Can Teach Themselves to Use Tools
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
Learning Transformer Programs
Membership Inference on Model Distillation
Nearly Tight Bounds For Differentially Private Multiway Cut
Online RL in Linearly q^piRealizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore
Optimal Sample Complexity for Learning Single Index Models
Orderingbased Conditions for Global Convergence of Policy Gradient Methods
PAC Learning and Online Learning
Privacy Auditing with One 1 Training Run
Private Everlasting Prediction
Provable InContext Learning with InContext Algorithm Selection
Random Cuts are Optimal for Explainable kMedians
Rethinking Parameter Counting in Statistical Learning
Rotating Features for Object Discovery
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent
Scaling DataConstrained Language Models
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization
Siamese Masked Autoencoders
Spatialfrequency channels
StraightThrough and Beyon
The Landscape of PolicyGradient Metho
The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation
Two Stories in Mechanistic Explanation of Neural Networks
Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation
Universal Algorithms
UserLevel Differential Privacy With Few Examples Per User
Visual Instruction Tuning
When Do Transformers Shine in RL Decoupling Memory from Credit Assignment
Why think step by step Reasoning emerges from the locality of experience
Your Language Model is Secretly a Reward Model

spotlight

3DLLM Injecting the 3D World into Large Language Models
4D Panoptic Scene Graph Generation
4M Massively Multimodal Masked Modeling
AbDiffuser fullatom generation of invitro functioning antibodies
Accelerated QuasiNewton Proximal Extragradient Faster Rate for Smooth Convex Optimization
Adaptive Data Analysis in a Balanced Adversarial Model
Adaptive whitening with fast gain modulation and slow synaptic plasticity
Adversarial Counterfactual Environment Model Learning
Adversarial Robustness in Graph Neural Networks A Hamiltonian Approach
Adversarial Training from Mean Field Perspective
AIMS AllInclusive MultiLevel Segmentation for Anything
Aleatoric and Epistemic Discrimination Fundamental Limits of Fairness Interventions
Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback
Alignment with human representations supports robust fewshot learning
Alleviating the Semantic Gap for Generalized fMRItoImage Reconstruction
AlpacaFarm A Simulation Framework for Methods that Learn from Human Feedback
Alternating Updates for Efficient Transformers
Alternation makes the adversary weaker in twoplayer games
AMDP An Adaptive Detection Procedure for False Discovery Rate Control in HighDimensional Mediation Analysis
Anonymous and CopyRobust Delegations for Liquid Democracy
An Alternating Optimization Method for Bilevel Problems under the Polyakojasiewicz Condition
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions
Approximate Heavy Tails in Offline MultiPass Stochastic Gradient Descent
ARTree A Deep Autoregressive Model for Phylogenetic Inference
Attentive Transfer Entropy to Exploit Transient Emergence of Coupling Effect
Auditing Fairness by Betting
Auditing for Human Expertise
A CrossMoment Approach for Causal Effect Estimation
A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability
A Dynamical System View of LangevinBased NonConvex Sampling
A GraphTheoretic Framework for Understanding OpenWorld SemiSupervised Learning
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation
A OneSizeFitsAll Approach to Improving Randomness in Paper Assignment
A PrivacyFriendly Approach to Data Valuation
A Robust and OpponentAware League Training Method for StarCraft II
A Scalable Neural Network for DSIC Affine Maximizer Auction Design
A Spectral Algorithm for ListDecodable Covariance Estimation in Relative Frobenius Norm
A Spectral Theory of Neural Prediction and Alignment
A Unified Generalization Analysis of ReWeighting and LogitAdjustment for Imbalanced Learning
Balancing memorization and generalization in RNNs for high performance brainmachine Interfaces
Banana Banach FixedPoint Network for Pointcloud Segmentation with InterPart Equivariance
Bayesian ExtensiveRank Matrix Factorization with Rotational Invariant Priors
Bayesian target optimisation for highprecision holographic optogenetics
Behavior Alignment via Reward Function Optimization
Best Arm Identification with Fixed Budget A Large Deviation Perspective
Beyond Myopia Learning from Positive and Unlabeled Data through Holistic Predictive Trends
Bifurcations and loss jumps in RNN training
Birth of a Transformer A Memory Viewpoint
Blockwise Parallel Transformers for Large Context Models
Bootstrapping VisionLanguage Learning with Decoupled Language Pretraining
Break It Down Evidence for Structural Compositionality in Neural Networks
Bypassing spike sorting Densitybased decoding using spike localization from dense multielectrode probes
Calibrated Stackelberg Games Learning Optimal Commitments Against Calibrated Agents
Can Language Models Solve Graph Problems in Natural Language
Can semisupervised learning use all the data effectively A lower bound perspective
Characterizing the Optimal 01 Loss for Multiclass Classification with a Testtime Attacker
CLIPOGD An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments
CODA Generalizing to Open and Unseen Domains with Compaction and Disambiguation
Coherent Soft Imitation Learning
Combating Representation Learning Disparity with Geometric Harmonization
Common Ground in Cooperative Communication
Complexity Matters Rethinking the Latent Space for Generative Modeling
Compression with Bayesian Implicit Neural Representations
Computing a humanlike reaction time metric from stable recurrent vision models
Conditional independence testing under misspecified inductive biases
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning
Conditional scorebased diffusion models for Bayesian inference in infinite dimensions
Conformal Prediction Sets for Ordinal Classification
Constant Approximation for Individual Preference Stable Clustering
ContextPIPs Persistent Independent Particles Demands Context Features
Continual Learning for Instruction Following from Realtime Feedback
Contrastive Lift 3D Object Instance Segmentation by SlowFast Contrastive Fusion
Convergence of Adam Under Relaxed Assumptions
Convergence of Alternating Gradient Descent for Matrix Factorization
Convex and Nonconvex Optimization Under Generalized Smoothness
Coop Memory is not a Commodity
Counterfactual Evaluation of PeerReview Assignment Policies
Counterfactual Memorization in Neural Language Models
Critical Initialization of Wide and Deep Neural Networks using Partial Jacobians General Theory and Applications
CS4ML A general framework for active learning with arbitrary data based on Christoffel functions
Curriculum Learning With Infant Egocentric Videos
Debias Coarsely, Sample Conditionally Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models
Decentralized Randomly Distributed Multiagent Multiarmed Bandit with Heterogeneous Rewards
Deep Fractional Fourier Transform
Deep Momentum MultiMarginal Schrdinger Bridge
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model
Deep Reinforcement Learning with Plasticity Injection
Delegated Classification
Demystifying Oversmoothing in AttentionBased Graph Neural Networks
Demystifying Softmax Gating Function in Gaussian Mixture of Experts
Dense and Aligned Captions DAC Promote Compositional Reasoning in VL Models
DeWave Discrete Encoding of EEG Waves for EEG to Text Translation
Differentiable Registration of Images and LiDAR Point Clouds with VoxelPointtoPixel Matching
Differentially Private Approximate Near Neighbor Counting in High Dimensions
Differentially Private Image Classification by Learning Priors from Random Processes
Diffusion Models and SemiSupervised Learners Benefit Mutually with Few Labels
Diffusion Schrdinger Bridge Matching
Diffusion with Forward Models Solving Stochastic Inverse Problems Without Direct Supervision
DIFUSCO Graphbased Diffusion Solvers for Combinatorial Optimization
DistanceRestricted Folklore WeisfeilerLeman GNNs with Provable Cycle Counting Power
Distributionally Robust Linear Quadratic Control
Distributionally Robust Skeleton Learning of Discrete Bayesian Networks
DistributionFree Statistical Dispersion Control for Societal Applications
Does Localization Inform Editing Surprising Differences in CausalityBased Localization vs. Knowledge Editing in Language Models
DoReMi Optimizing Data Mixtures Speeds Up Language Model Pretraining
Double Gumbel QLearning
DPOK Reinforcement Learning for Finetuning TexttoImage Diffusion Models
DreamHuman Animatable 3D Avatars from Text
DreamSim Learning New Dimensions of Human Visual Similarity using Synthetic Data
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers
Dynamic Tensor Decomposition via Neural DiffusionReaction Processes
Effective HumanAI Teams via Learned Natural Language Rules and Onboarding
Efficient Adversarial Contrastive Learning via RobustnessAware Coreset Selection
Efficient Online Clustering with Moving Costs
EmbodiedGPT VisionLanguage PreTraining via Embodied Chain of Thought
Encoding TimeSeries Explanations through SelfSupervised Model Behavior Consistency
Episodic MultiTask Learning with Heterogeneous Neural Processes
Epistemic Neural Networks
Equivariant Neural Operator Learning with Graphon Convolution
Error Bounds for Learning with VectorValued Random Features
Evaluating and Inducing Personality in Pretrained Language Models
Evaluating the Moral Beliefs Encoded in LLMs
Explaining the Uncertain Stochastic Shapley Values for Gaussian Process Models
Explore InContext Learning for 3D Point Cloud Understanding
Exploring Geometry of Blind Spots in Vision models
Exploring Loss Functions for Timebased Training Strategy in Spiking Neural Networks
Exposing Attention Glitches with FlipFlop Language Modeling
Expressive Sign Equivariant Networks for Spectral Geometric Learning
Extraction and Recovery of SpatioTemporal Structure in Latent Dynamics Alignment with Diffusion Model
Faith and Fate Limits of Transformers on Compositionality
Faster Margin Maximization Rates for Generic Optimization Methods
Fast Approximation of Similarity Graphs with Kernel Density Estimation
Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics
Feature Adaptation for Sparse Linear Regression
FineGrained Human Feedback Gives Better Rewards for Language Model Training
Followups Also Matter Improving Contextual Bandits via Postserving Contexts
For SALE StateAction Representation Learning for Deep Reinforcement Learning
From Pixels to UI Actions Learning to Follow Instructions via Graphical User Interfaces
From Tempered to Benign Overfitting in ReLU Neural Networks
FullAtom Protein Pocket Design via Iterative Refinement
FutureDependent ValueBased OffPolicy Evaluation in POMDPs
Gaussian Partial Information Decomposition Bias Correction and Application to Highdimensional Data
Generalization in the Face of Adaptivity A Bayesian Perspective
Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems
GLIME General, Stable and Local LIME Explanation
GloptiNets Scalable NonConvex Optimization with Certificates
Grounding Neural Inference with Satisfiability Modulo Theories
Group Fairness in Peer Review
Hierarchically Gated Recurrent Neural Network for Sequence Modeling
Hierarchical clustering with dot products recovers hidden tree structure
Hierarchical Decomposition of PromptBased Continual Learning Rethinking Obscured Suboptimality
Hierarchical Integration Diffusion Model for Realistic Image Deblurring
Highdimensional Asymptotics of Denoising Autoencoders
HighFidelity Audio Compression with Improved RVQGAN
HIQL Offline GoalConditioned RL with Latent States as Actions
Honesty Is the Best Policy Defining and Mitigating AI Deception
How to Scale Your EMA
HyenaDNA LongRange Genomic Sequence Modeling at Single Nucleotide Resolution
Hypernetworkbased MetaLearning for LowRank PhysicsInformed Neural Networks
HyTrel Hypergraphenhanced Tabular Data Representation Learning
ID and OOD Performance Are Sometimes Inversely Correlated on Realworld Datasets
Imitation Learning from Imperfection Theoretical Justifications and Algorithms
Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability
Implicit Variational Inference for HighDimensional Posteriors
Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise
Improved Frequency Estimation Algorithms with and without Predictions
<a href=http://doc.flyingfry.cc/NIPS2023/spotlight/InContext_Impersonation_Reveals_Large_Language_Models'_Strengths_and_Biases.pdf>InContext Impersonation Reveals Large Language Models' Strengths and Biases
InContext Learning Unlocked for Diffusion Models
Individual Arbitrariness and Group Fairness
InferenceTime Intervention Eliciting Truthful Answers from a Language Model
Inferring the Future by Imagining the Past
Information Maximization Perspective of Orthogonal Matching Pursuit with Applications to Explainable AI
Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction
Invariant Learning via Probability of Sufficient and Necessary Causes
Is Learning in Games Good for the Learners
Is This Loss Informative Faster TexttoImage Customization by Tracking Objective Dynamics
Kernelized Cumulants Beyond Kernel Mean Embeddings
Kernel Quadrature with Randomly Pivoted Cholesky
Kiki or Bouba Sound Symbolism in VisionandLanguage Models
KroneckerFactored Approximate Curvature for Modern Neural Network Architectures
LayoutGPT Compositional Visual Planning and Generation with Large Language Models
LCAD Languagebased Colorization with Anylevel Descriptions using Diffusion Priors
Learning from Active Human Involvement through Proxy Value Propagation
Learning Functional Transduction
Learning Generalizable Agents via Saliencyguided Features Decorrelation
Learning Layerwise Equivariances Automatically using Gradients
Learning ListLevel DomainInvariant Representations for Ranking
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
Learning to Discover Skills through Guidance
Learning to Receive Help InterventionAware Concept Embedding Models
Learning Universal Policies via TextGuided Video Generation
Let the Flows Tell Solving Graph Combinatorial Problems with GFlowNets
Leveraging sparse and shared feature activations for disentangled representation learning
Lexinvariant Language Models
LinkerNet Fragment Poses and Linker CoDesign with 3D Equivariant Diffusion
List and Certificate Complexities in Replicable Learning
Locality Sensitive Hashing in Fourier Frequency Domain For Soft Set Containment Search
Masked SpaceTime Hash Encoding for Efficient Dynamic Scene Reconstruction
Maximization of Average Precision for Deep Learning with Adversarial Ranking Robustness
Maximize to Explore One Objective Function Fusing Estimation, Planning, and Exploration
MaxMargin Token Selection in Attention Mechanism
Meanfield Langevin dynamics Timespace discretization, stochastic gradient, and variance reduction
Mechanism Design for Collaborative Normal Mean Estimation
MeCo ZeroShot NAS with One Data and Single Forward Pass via Minimum Eigenvalue of Correlation
Memory Efficient Optimizers with 4bit States
MGDD A Meta Generator for Fast Dataset Distillation
MinimumRisk Recalibration of Classifiers
Mitigating the Popularity Bias of Graph Collaborative Filtering A Dimensional Collapse Perspective
MMDFuse Learning and Combining Kernels for TwoSample Testing Without Data Splitting
Model Sparsity Can Simplify Machine Unlearning
Model Spider Learning to Rank PreTrained Models Efficiently
MultiObject Representation Learning via Feature Connectivity and ObjectCentric Regularization
Multi Time Scale World Models
MVDiffusion Enabling Holistic Multiview Image Generation with CorrespondenceAware Diffusion
Nearoptimal learning with average Hlder smoothness
Neural Foundations of Mental Simulation Future Prediction of Latent Representations on Dynamic Scenes
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem
Newton Cotes Graph Neural Networks On the Time Evolution of Dynamic Systems
NonAsymptotic Analysis of a UCBbased Top Two Algorithm
Normalizing flow neural networks by JKO scheme
No Change, No Gain Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning
ObjectCentric Slot Diffusion
OKRidge Scalable Optimal kSparse Ridge Regression
Onestep differentiation of iterative algorithms
One Fits All Power General Time Series Analysis by Pretrained LM
Online Constrained MetaLearning Provable Guarantees for Generalization
Online Control for Metaoptimization
Online Label Shift Optimal Dynamic Regret meets Practical Algorithms
Online List Labeling with Predictions
Online Multinomial Logistic Bandit Improved Regret and Constant Computation Cost
On Learning Necessary and Sufficient Causal Graphs
On quantum backpropagation, information reuse, and cheating measurement collapse
On the Connection between Pretraining Data Diversity and Finetuning Robustness
On the Giniimpurity Preservation For Privacy Random Forests
On the Learnability of Multilabel Ranking
On the Minimax Regret for Online Learning with Feedback Graphs
On the Planning Abilities of Large Language Models A Critical Investigation
On the Role of Randomization in Adversarially Robust Classification
On the Variance, Admissibility, and Stability of Empirical Risk Minimization
Optimal Exploration for ModelBased RL in Nonlinear Systems
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
Optimistic Natural Policy Gradient a Simple Efficient Policy Optimization Framework for Online RL
Optimizing Prompts for TexttoImage Generation
OutlierRobust GromovWasserstein for Graph Data
PAC Learning Linear Thresholds from Label Proportions
PAPR Proximity Attention Point Rendering
Parallel Sampling of Diffusion Models
Parallel Submodular Function Minimization
Pareto Frontiers in Deep Feature Learning Data, Compute, Width, and Luck
Parsel Algorithmic Reasoning with Language Models by Composing Decompositions
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
Participatory Personalization in Classification
Paxion Patching Action Knowledge in VideoLanguage Foundation Models
PDERefiner Achieving Accurate Long Rollouts with Neural PDE Solvers
PhysicsDriven MLBased Modelling for Correcting Inverse Estimation
PlugandPlay Stability for Intracortical BrainComputer Interfaces A OneYear Demonstration of Seamless BraintoText Communication
Posterior Contraction Rates for Matrn Gaussian Processes on Riemannian Manifolds
Practical SharpnessAware Minimization Cannot Converge All the Way to Optima
Precise asymptotic generalization for multiclass classification with overparameterized linear models
PrefixTree Decoding for Predicting Mass Spectra from Molecules
PreRMSNorm and PreCRMSNorm Transformers Equivalent and Efficient PreLN Transformers
PreTraining Protein Encoder via Siamese SequenceStructure Diffusion Trajectory Prediction
PrincipleDriven SelfAlignment of Language Models from Scratch with Minimal Human Supervision
Privacy Assessment on Reconstructed Images Are Existing Evaluation Metrics Faithful to Human Perception
Private Distribution Learning with Public Data The View from Sample Compression
Private estimation algorithms for stochastic block models and mixture models
Private Stochastic NonConvex Optimization Revisited SecondOrder Stationary Points and Excess Risks
PRODIGY Enabling Incontext Learning Over Graphs
ProlificDreamer HighFidelity and Diverse Textto3D Generation with Variational Score Distillation
Promises and Pitfalls of Thresholdbased Autolabeling
ProPILE Probing Privacy Leakage in Large Language Models
Protein Design with Guided Discrete Diffusion
Provable benefits of annealing for estimating normalizing constants Importance Sampling, NoiseContrastive Estimation, and beyon
Provable benefits of score matching
Provable Guarantees for Nonlinear Feature Learning in ThreeLayer Neural Networks
Provable Training for Graph Contrastive Learning
Provably Bounding Neural Network Preimages
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation
ProximityInformed Calibration for Deep Neural Networks
Puzzlefusion Unleashing the Power of Diffusion Models for Spatial Puzzle Solving
QuACK Accelerating GradientBased Quantum Optimization with Koopman Operator Learning
QuantSR Accurate Lowbit Quantization for Efficient Image SuperResolution
QuasiMonte Carlo Graph Random Features
QuIP 2Bit Quantization of Large Language Models With Guarantees
Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks
RankNContrast Learning Continuous Representations for Regression
RealWorld Image Variation by Aligning Diffusion Inversion Chain
<a href=http://doc.flyingfry.cc/NIPS2023/spotlight/Reconstructing_the_Mind's_Eye_fMRItoImage_with_Contrastive_Learning_and_Diffusion_Priors.pdf>Reconstructing the Mind's Eye fMRItoImage with Contrastive Learning and Diffusion Priors
Regret Matching+ InStability and Fast Convergence in Games
Regularization properties of adversariallytrained linear regression
Regularized Behavior Cloning for Blocking the Leakage of Past Action Information
ReinforcementEnhanced Autoregressive Feature Transformation Gradientsteered Search in Continuous Space for Postfix Expressions
Relax, it doesnt matter how you get there A new selfsupervised approach for multitimescale behavior analysis
RePo Resilient ModelBased Reinforcement Learning by Regularizing Posterior Predictability
ResShift Efficient Diffusion Model for Image Superresolution by Residual Shifting
Restless Bandits with Average Reward Breaking the Uniform Global Attractor Assumption
Rewiring Neurons in NonStationary Environments
RiskAverse Active Sensing for Timely Outcome Prediction under Cost Pressure
Robust Distributed Learning Tight Error Bounds and Breakdown Point under Data Heterogeneity
Robust Model Reasoning and Fitting via Dual Sparsity Pursuit
SaddletoSaddle Dynamics in Diagonal Linear Networks
Safety Verification of DecisionTree Policies in Continuous Time
SAME Uncovering GNN Black Box with Structureaware Shapleybased Multipiece Explanations
Sample Complexity of Forecast Aggregation
Sample Efficient Reinforcement Learning in Mixed Systems through Augmented Samples and Its Applications to Queueing Networks
Scale Alone Does not Improve Mechanistic Interpretability in Vision Models
Scaling OpenVocabulary Object Detection
Schemalearning and rebinding as mechanisms of incontext learning and emergence
Scorebased Generative Modeling through Stochastic Evolution Equations in Hilbert Spaces
Scorebased Generative Models with Lvy Processes
SE3 Equivariant Augmented Coupling Flows
SE3 Equivariant Convolution and Transformer in Ray Space
Segment Any Point Cloud Sequences by Distilling Vision Foundation Models
Selective Amnesia A Continual Learning Approach to Forgetting in Deep Generative Models
SemiSupervised Domain Generalization with Known and Unknown Classes
Separable PhysicsInformed Neural Networks
Sharp Spectral Rates for Koopman Operator Learning
Should I Stop or Should I Go Early Stopping with Heterogeneous Populations
SimFBO Towards Simple, Flexible and Communicationefficient Federated Bilevel Learning
SimMTM A Simple PreTraining Framework for Masked TimeSeries Modeling
Skillit! A datadriven skills framework for understanding and training language models
SlotDiffusion ObjectCentric Generative Modeling with Diffusion Models
Slow and Weak Attractor Computation Embedded in Fast and Strong EI Balanced Neural Dynamics
Smoothed Analysis of Sequential Probability Assignment
Smoothed Online Learning for Prediction in Piecewise Affine Systems
Sounding Bodies Modeling 3D Spatial Sound of Humans Using Body Pose and Audio
SPAE Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs
Spuriosity Rankings Sorting Data to Measure and Mitigate Biases
Squared Neural Families A New Class of Tractable Density Models
Squeeze, Recover and Relabel Dataset Condensation at ImageNet Scale From A New Perspective
Stable Diffusion is Unstable
Stable NonconvexNonconcave Training via Linear Interpolation
State Sequences Prediction via Fourier Transform for Representation Learning
Statistical Guarantees for Variational Autoencoders using PACBayesian Theory
Stein PiImportance Sampling
STEVE1 A Generative Model for TexttoBehavior in Minecraft
Stochastic Multiarmed Bandits Optimal Tradeoff among Optimality, Consistency, and Tail Risk
Streaming PCA for Markovian Data
Structurefree Graph Condensation From Largescale Graphs to Condensed Graphfree Data
Subspace Identification for MultiSource Domain Adaptation
Supervised Pretraining Can Learn InContext Reinforcement Learning
Survival Instinct in Offline Reinforcement Learning
SwiftSage A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks
Temperature Balancing, Layerwise Weight Analysis, and Neural Network Training
TexttoImage Diffusion Models are Zero Shot Classifiers
Theoretical and Practical Perspectives on what Influence Functions Do
The Behavior and Convergence of Local Bayesian Optimization
The Equivalence of Dynamic and Strategic Stability under Regularized Learning in Games
The Exact Sample Complexity Gain from Invariances for Kernel Regression
<a href=http://doc.flyingfry.cc/NIPS2023/spotlight/The_Geometry_of_Neural_Nets'_Parameter_Spaces_Under_Reparametrization.pdf>The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
The Goldilocks of Pragmatic Understanding FineTuning Strategy Matters for Implicature Resolution by LLMs
The PicktoLearn Algorithm Empowering Compression for Tight Generalization Bounds and Improved Posttraining Performance
The Pursuit of Human Labeling A New Perspective on Unsupervised Learning
The Rashomon Importance Distribution Getting RID of Unstable, Single Modelbased Variable Importance
Thought Cloning Learning to Think while Acting by Imitating Human Thinking
Three Iterations of d 1WL Test Distinguish Non Isometric Clouds of ddimensional Points
Tight Risk Bounds for Gradient Descent on Separable Data
Timewarp Transferable Acceleration of Molecular Dynamics by Learning TimeCoarsened Dynamics
Topological Parallax A Geometric Specification for Deep Perception Models
Towards Automated Circuit Discovery for Mechanistic Interpretability
Towards Incontext Scene Understanding
Towards Robust and Expressive Wholebody Human Pose and Shape Estimation
Towards SymmetryAware Generation of Periodic Materials
Towards TestTime Refusals via Concept Negation
Tracr Compiled Transformers as a Laboratory for Interpretability
Training shallow ReLU networks on noisy data using hinge loss when do we overfit and is it benign
Train Once, Get a Family StateAdaptive Balances for OfflinetoOnline Reinforcement Learning
TransDimensional Generative Modeling via Jump Diffusion Models
Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction
Transitionconstant Normalization for Image Enhancement
TreeBased Diffusion Schrdinger Bridge with Applications to Wasserstein Barycenters
Tree Variational Autoencoders
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks
Uncovering motifs of concurrent signaling across multiple neuronal populations
Uncovering the Hidden Dynamics of Video Selfsupervised Learning under Distribution Shifts
Understanding Multiphase Optimization Dynamics and Rich Nonlinear Behaviors of ReLU Networks
Unexpected Improvements to Expected Improvement for Bayesian Optimization
Unified Embedding BattleTested Feature Representations for WebScale ML Systems
Unifying Predictions of Deterministic and Stochastic Physics in Meshreduced Space with Sequential Flow Generative Model
Universal Online Learning with Gradient Variations A Multilayer Online Ensemble Approach
Unpaired MultiDomain Causal Representation Learning
VaRT Variational Regression Trees
Visual Explanations of ImageText Representations via MultiModal Information Bottleneck Attribution
VoxDet Voxel Learning for Novel Instance Detection
Vulnerabilities in Video Quality Assessment Models The Challenge of Adversarial Attacks
Wasserstein Quantum Monte Carlo A Novel Approach for Solving the Quantum ManyBody Schrdinger Equation
What Makes Data Suitable for a Locally Connected Neural Network A Necessary and Sufficient Condition Based on Quantum Entanglement
What Planning Problems Can A Relational Neural Network Solve
When Does Optimizing a Proper Loss Yield Calibration
Which Models have PerceptuallyAligned Gradients An Explanation via OffManifold Robustness
WITRAN Waterwave Information Transmission and Recurrent Acceleration Network for Longrange Time Series Forecasting
Would I have gotten that reward Longterm credit assignment by counterfactual contribution analysis
Zeroshot causal learning
ZoomTrack Targetaware Nonuniform Resizing for Efficient Visual Tracking

poster

2Direction Theoretically Faster Distributed Training with Bidirectional Communication Compression
3DAware Visual Question Answering about Parts, Poses and Occlusions
3DIntPhys Towards More Generalized 3Dgrounded Visual Intuitive Physics under Challenging Scenes
3D CopyPaste Physically Plausible Object Insertion for Monocular 3D Detection
3D Indoor Instance Segmentation in an OpenWorl
3D molecule generation by denoising voxel grids
A3FL Adversarially Adaptive Backdoor Attacks to Federated Learning
Accelerated OnDevice Forward Neural Network Training with ModuleWise Descending Asynchronism
Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation
Accelerated Zerothorder Method for NonSmooth Stochastic Convex Optimization Problem with Infinite Variance
Accelerating Exploration with Unlabeled Prior Data
Accelerating Molecular Graph Neural Networks via Knowledge Distillation
Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction
Accelerating Motion Planning via Optimal Transport
Accelerating Reinforcement Learning with ValueConditional State Entropy Exploration
Accelerating Value Iteration with Anchoring
Accessing Higher Dimensions for Unsupervised Word Translation
Accountability in Offline Reinforcement Learning Explaining Decisions with a Corpus of Examples
Accurate Interpolation for Scattered Data through Hierarchical Residual Refinement
Achieving Cross Modal Generalization with Multimodal Unified Representation
Achieving mathcalOepsilon^1.5 Complexity in HessianJacobianfree Stochastic Bilevel Optimization
Action Inference by Maximising Evidence ZeroShot Imitation from Observation with World Models
Actively Testing Your Model While It Learns Realizing LabelEfficient Learning in Practice
Active Bipartite Ranking
Active LearningBased Species Range Estimation
Active Learning for Semantic Segmentation with Multiclass Label Query
Active Negative Loss Functions for Learning with Noisy Labels
Active Observing in Continuoustime Control
Active Reasoning in an OpenWorld Environment
Active representation learning for general task space with applications in robotics
Active Vision Reinforcement Learning under Limited Visual Observability
Activity Grammars for Temporal Action Segmentation
Act As You Wish FineGrained Control of Motion Diffusion Model with Hierarchical Semantic Graphs
AdANNS A Framework for Adaptive Semantic Search
AdaPlanner Adaptive Planning from Feedback with Language Models
Adapting Fairness Interventions to Missing Values
Adapting Neural Link Predictors for DataEfficient Complex Query Answering
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation
Adaptive Algorithms for Relaxed Pareto Set Identification
Adaptive Contextual Perception How To Generalize To New Backgrounds and Ambiguous Objects
Adaptive Linear Estimating Equations
Adaptive Normalization for Nonstationary Time Series Forecasting A Temporal Slice Perspective
Adaptive Online Replanning with Diffusion Models
Adaptive Principal Component Regression with Applications to Panel Data
Adaptive Privacy Composition for Accuracyfirst Mechanisms
Adaptive recurrent vision performs zeroshot computation scaling to unseen difficulty levels
Adaptive Selective Sampling for Online Prediction with Experts
Adaptive SGD with Polyak stepsize and Linesearch Robust Convergence and Variance Reduction
Adaptive TestTime Personalization for Federated Learning
Adaptive Topological Feature via Persistent Homology Filtration Learning for Point Clouds
Adaptive Uncertainty Estimation via HighDimensional Testing on Latent Representations
AdaptSSR Pretraining User Model with AugmentationAdaptive SelfSupervised Ranking
AdaVAE Bayesian Structural Adaptation for Variational Autoencoders
Addressing Negative Transfer in Diffusion Models
Addressing the speedaccuracy simulation tradeoff for adaptive spiking neurons
Add and Thin Diffusion for Temporal Point Processes
Adjustable Robust Reinforcement Learning for Online 3D Bin Packing
ADPT Autonomous Driving PreTraining with Largescale Point Cloud Dataset
Advancing Bayesian Optimization via Learning Correlated Latent Space
Adversarially Robust Distributed Count Tracking via Partial Differential Privacy
Adversarially Robust Learning with Uncertain Perturbation Sets
Adversarial Attacks on Online Learning to Rank with Click Feedback
Adversarial Examples Are Not Real Features
Adversarial Examples Exist in TwoLayer ReLU Networks for Low Dimensional Linear Subspaces
Adversarial Examples Might be Avoidable The Role of Data Concentration in Adversarial Robustness
Adversarial Learning for Feature Shift Detection and Correction
Adversarial Model for Offline Reinforcement Learning
Adversarial Resilience in Sequential Prediction via Abstention
Adversarial Robustness through Random Weight Sampling
Adversarial SelfTraining Improves Robustness and Generalization for Gradual Domain Adaptation
Adversarial Training for Graph Neural Networks Pitfalls, Solutions, and New Directions
Advice Querying under Budget Constraint for Online Algorithms
AffinityAware Graph Networks
AGD an Autoswitchable Optimizer using Stepwise Gradient Difference for Preconditioning Matrix
Aggregating Capacity in FL through Successive Layer Training for ComputationallyConstrained Devices
Aging with GRACE Lifelong Model Editing with Discrete KeyValue Adaptors
Agnostically Learning SingleIndex Models using Omnipredictors
Agnostic MultiGroup Active Learning
AiluRus A Scalable ViT Framework for Dense Prediction
Aiming towards the minimizers fast convergence of SGD for overparametrized problems
AI for Interpretable Chemistry Predicting Radical Mechanistic Pathways via Contrastive Learning
AlberDICE Addressing OutOfDistribution Joint Actions in Offline MultiAgent RL via Alternating Stationary Distribution Correction Estimation
Algorithmic Regularization in Tensor Optimization Towards a Lifted Approach in Matrix Sensing
Algorithm Selection for Deep Active Learning with Imbalanced Datasets
ALGO Synthesizing Algorithmic Programs with Generated Oracle Verifiers
Aligning Gradient and Hessian for Neural Signed Distance Function
Aligning Language Models with Human Preferences via a Bayesian Approach
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation
Align Your Prompts TestTime Prompting with Distribution Alignment for ZeroShot Generalization
ALIM Adjusting Label Importance Mechanism for Noisy Partial Label Learning
All Points Matter EntropyRegularized Distribution Alignment for Weaklysupervised 3D Segmentation
Almost Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
Alternating Gradient Descent and MixtureofExperts for Integrated Multimodal Perception
AmadeusGPT a natural language interface for interactive animal behavioral analysis
AMAG Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity
Ambient Diffusion Learning Clean Distributions from Corrupted Data
Amortized Reparametrization Efficient and Scalable Variational Inference for Latent SDEs
Amplified Banded Matrix Factorization A unified approach to private training
Analysis of Variance of Multiple Causal Networks
Analyzing Generalization of Neural Networks through Loss Path Kernels
Analyzing the Sample Complexity of SelfSupervised Image Reconstruction Methods
Analyzing Vision Transformers for Image Classification in Class Embedding Space
Anchor Data Augmentation
AND Adversarial Neural Degradation for Learning Blind Image SuperResolution
ANeSI A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
ANet A Scalable Pathbased Reasoning Approach for Knowledge Graphs
Annotator A Generic Active Learning Baseline for LiDAR Semantic Segmentation
Anonymous Learning via LookAlike Clustering A Precise Analysis of Model Generalization
ANPL Towards Natural Programming with Interactive Decomposition
ANTN Bridging Autoregressive Neural Networks and Tensor Networks for Quantum ManyBody Simulation
AnytimeCompetitive Reinforcement Learning with Policy Prior
Anytime Model Selection in Linear Bandits
AnytoAny Generation via Composable Diffusion
An active learning framework for multigroup mean estimation
An Adaptive Algorithm for Learning with Unknown Distribution Drift
An Alternative to Variance Gini Deviation for Riskaverse Policy Gradient
An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint
An Efficient Dataset Condensation Plugin and Its Application to Continual Learning
An Efficient DoublyRobust Test for the Kernel Treatment Effect
An Efficient EndtoEnd Training Approach for ZeroShot HumanAI Coordination
An Empirical Study Towards PromptTuning for Graph Contrastive PreTraining in Recommendations
An ExplorationbyOptimization Approach to Best of Both Worlds in Linear Bandits
An Improved Relaxation for OracleEfficient Adversarial Contextual Bandits
An Inductive Bias for Tabular Deep Learning
An InformationTheoretic Evaluation of Generative Models in Learning Multimodal Distributions
An informationtheoretic quantification of the content of communication between brain regions
An Information Theory Perspective on VarianceInvarianceCovariance Regularization
An Inverse Scaling Law for CLIP Training
An Iterative SelfLearning Framework for Medical Domain Generalization
An Optimal Structured Zerothorder Algorithm for Nonsmooth Optimization
An Optimizationbased Approach To Node Role Discovery in Networks Approximating Equitable Partitions
An varepsilonBestArm Identification Algorithm for FixedConfidence and Beyon
Approximately Equivariant Graph Networks
Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders
Approximate inference of marginals using the IBIA framework
ApproximationGeneralization Tradeoffs under Approximate Group Equivariance
Arbitrarily Scalable Environment Generators via Neural Cellular Automata
Architecture Matters Uncovering Implicit Mechanisms in Graph Contrastive Learning
ARDiffusion AutoRegressive Diffusion Model for Text Generation
Are aligned neural networks adversarially aligne
Are Diffusion Models VisionAndLanguage Reasoners
Are GATs Out of Balance
Are Vision Transformers More Data Hungry Than Newborn Visual Systems
ARTIC3D Learning Robust Articulated 3D Shapes from Noisy Web Image Collections
ASIF Coupled Data Turns Unimodal Models to Multimodal without Training
ASPEN Breaking Operator Barriers for Efficient Parallelization of Deep Neural Networks
Assessor360 Multisequence Network for Blind Omnidirectional Image Quality Assessment
Assumption violations in causal discovery and the robustness of score matching
Asymmetric Certified Robustness via FeatureConvex Neural Networks
Asymptotically Optimal Quantile Pure Exploration for InfiniteArmed Bandits
Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression
Asynchronous Proportional Response Dynamics Convergence in Markets with Adversarial Scheduling
<a href=http://doc.flyingfry.cc/NIPS2023/poster/AsynchronyRobust_Collaborative_Perception_via_Bird's_Eye_View_Flow.pdf>AsynchronyRobust Collaborative Perception via Bird's Eye View Flow
ATMAN Understanding Transformer Predictions Through Memory Efficient Attention Manipulation
Attacks on Online Learners a TeacherStudent Analysis
ATTA Anomalyaware TestTime Adaptation for OutofDistribution Detection in Segmentation
Attention as Implicit Structural Inference
AUDIT Audio Editing by Following Instructions with Latent Diffusion Models
AugmentationAware SelfSupervision for DataEfficient GAN Training
Augmentationfree Dense Contrastive Distillation for Efficient Semantic Segmentation
Augmented Memory Replaybased Continual Learning Approaches for Network Intrusion Detection
Augmenting Language Models with LongTerm Memory
Autodecoding Latent 3D Diffusion Models
AutoGO Automated Computation Graph Optimization for Neural Network Evolution
Automated Classification of Model Errors on ImageNet
Automatic Clipping Differentially Private Deep Learning Made Easier and Stronger
Automatic Grouping for Efficient Cooperative MultiAgent Reinforcement Learning
Automatic Integration for Spatiotemporal Neural Point Processes
Autonomous Capability Assessment of Sequential DecisionMaking Systems in Stochastic Settings
Auxiliary Losses for Learning Generalizable Conceptbased Models
AVIS Autonomous Visual Information Seeking with Large Language Model Agent
AVNeRF Learning Neural Fields for RealWorld AudioVisual Scene Synthesis
A BatchtoOnline Transformation under RandomOrder Model
A Bayesian Approach To Analysing Training Data Attribution In Deep Learning
A Bayesian Take on Gaussian Process Networks
A Bounded Ability Estimation for Computerized Adaptive Testing
A case for reframing automated medical image classification as segmentation
A Causal Framework for Decomposing Spurious Variations
A Closer Look at the Robustness of Contrastive LanguageImage PreTraining CLIP
A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings
A Competitive Algorithm for Agnostic Active Learning
A Computationally Efficient Sparsified Online Newton Metho
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting
A DataFree Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks
A Definition of Continual Reinforcement Learning
A DiffusionModel of Joint Interactive Navigation
A DualStream Neural Network Explains the Functional Segregation of Dorsal and Ventral Visual Pathways in Human Brains
A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging
A fast heuristic to optimize timespace tradeoff for large models
A FiniteParticle Convergence Rate for Stein Variational Gradient Descent
A FiniteSample Analysis of PayoffBased Independent Learning in ZeroSum Stochastic Games
A Fractional Graph Laplacian Approach to Oversmoothing
A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions
A General Framework for Equivariant Neural Networks on Reductive Lie Groups
A General Framework for Robust GInvariance in GEquivariant Networks
A General Theory of Correct, Incorrect, and Extrinsic Equivariance
A generative model of the hippocampal formation trained with theta driven local learning rules
A graphonsignal analysis of graph neural networks
A Guide Through the Zoo of Biased SGD
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction
A HeavyTailed Algebra for Probabilistic Programming
A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space
A Hierarchical Training Paradigm for Antibody Structuresequence Codesign
A Logic for Expressing LogPrecision Transformers
A Long Nstep Surrogate Stage Reward for Deep Reinforcement Learning
A MetadataDriven Approach to Understand Graph Neural Networks
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks
A new perspective on building efficient and expressive 3D equivariant graph neural networks
A normative theory of social conflict
A Novel Approach for Effective MultiView Clustering with InformationTheoretic Perspective
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
A PartiallySupervised Reinforcement Learning Framework for Visual Active Search
A Path to Simpler Models Starts With Noise
A polar prediction model for learning to represent visual transformations
A PseudoSemantic Loss for Autoregressive Models with Logical Constraints
A Randomized Approach to Tight Privacy Accounting
A Recurrent Neural Circuit Mechanism of Temporalscaling Equivariant Representation
A Reductionbased Framework for Sequential Decision Making with Delayed Feedback
A Regularized Conditional GAN for Posterior Sampling in Image Recovery Problems
A Riemannian Exponential Augmented Lagrangian Method for Computing the Projection Robust Wasserstein Distance
A Robust Exact Algorithm for the Euclidean Bipartite Matching Problem
A ScaleInvariant Sorting Criterion to Find a Causal Order in Additive Noise Models
A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm
A Single 2D Pose with Context is Worth Hundreds for 3D Human Pose Estimation
A Smooth Binary Mechanism for Efficient Private Continual Observation
A State Representation for Diminishing Rewards
A SublinearTime Spectral Clustering Oracle with Improved Preprocessing Time
A Tale of Two Features Stable Diffusion Complements DINO for ZeroShot Semantic Correspondence
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
A Theoretical Analysis of the Test Error of FiniteRank Kernel Ridge Regression
A Theory of Link Prediction via Relational WeisfeilerLeman on Knowledge Graphs
A Theory of Multimodal Learning
A Theory of TransferBased BlackBox Attacks Explanation and Implications
A Theory of Unsupervised Translation Motivated by Understanding Animal Communication
A Trichotomy for Transductive Online Learning
A Unified, Scalable Framework for Neural Population Decoding
A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process
A Unified Approach for Maximizing Continuous DRsubmodular Functions
A Unified Approach to CountBased Weakly Supervised Learning
A Unified Approach to Domain Incremental Learning with Memory Theory and Algorithm
A Unified Conditional Framework for Diffusionbased Image Restoration
A Unified Detection Framework for InferenceStage Backdoor Defenses
A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
A Unified Fast Gradient Clipping Framework for DPSGD
A unified framework for informationtheoretic generalization bounds
A Unified Framework for Rankbased Loss Minimization
A Unified Framework for UNet Design and Analysis
A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing
A Unified Model and Dimension for Interactive Estimation
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning
A Unifying Perspective on MultiCalibration Game Dynamics for MultiObjective Learning
A Variational Perspective on HighResolution ODEs
BackModality Leveraging Modal Transformation for Data Augmentation
BadTrack A PoisonOnly Backdoor Attack on Visual Object Tracking
Balance, Imbalance, and Rebalance Understanding Robust Overfitting from a Minimax Game Perspective
Balanced Training for Sparse GANs
Balancing Risk and Reward A BatchedBandit Strategy for Automated Phased Release
BanditPAM++ Faster kmedoids Clustering
Bandit Social Learning under Myopic Behavior
Bandit Task Assignment with Unknown Processing Time
BasisFormer Attentionbased Time Series Forecasting with Learnable and Interpretable Basis
Batchnorm Allows Unsupervised Radial Attacks
Batch Bayesian Optimization For Replicable Experimental Design
BayesDAG GradientBased Posterior Inference for Causal Discovery
Bayesian Active Causal Discovery with MultiFidelity Experiments
Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite StateSpace
Bayesian Learning via QExponential Process
Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval
Bayesian nonparametric nonrenewal processes for analyzing neural spike train variability
Bayesian Optimisation of Functions on Graphs
Bayesian Optimization with Costvarying Variable Subsets
Bayesian RiskAverse QLearning with Streaming Observations
BayesTune Bayesian Sparse Deep Model Finetuning
Bayes beats Cross Validation Efficient and Accurate Ridge Regression via Expectation Maximization
BCDiff Bidirectional Consistent Diffusion for Instantaneous Trajectory Prediction
Belief ProjectionBased Reinforcement Learning for Environments with Delayed Feedback
<a href=http://doc.flyingfry.cc/NIPS2023/poster/BERT_Lost_Patience_Won't_Be_Robust_to_Adversarial_Slowdown.pdf>BERT Lost Patience Won't Be Robust to Adversarial Slowdown
Beta Diffusion
Better Correlation and Robustness A DistributionBalanced SelfSupervised Learning Framework for Automatic Dialogue Evaluation
Better Private Linear Regression Through Better Private Feature Selection
Better with Less A DataActive Perspective on PreTraining Graph Neural Networks
Beyond Average Return in Markov Decision Processes
Beyond BlackBox Advice LearningAugmented Algorithms for MDPs with QValue Predictions
Beyond Confidence Reliable Models Should Also Consider Atypicality
Beyond Deep Ensembles A LargeScale Evaluation of Bayesian Deep Learning under Distribution Shift
Beyond Exponential Graph CommunicationEfficient Topologies for Decentralized Learning via Finitetime Convergence
Beyond Geometry Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis
Beyond Invariance TestTime LabelShift Adaptation for Addressing Spurious Correlations
Beyond MLE Convex Learning for Text Generation
Beyond Normal On the Evaluation of Mutual Information Estimators
Beyond NTK with Vanilla Gradient Descent A MeanField Analysis of Neural Networks with Polynomial Width, Samples, and Time
Beyond Pretrained Features Noisy Image Modeling Provides Adversarial Defense
Beyond probability partitions Calibrating neural networks with semantic aware grouping
Beyond Uniform Sampling Offline Reinforcement Learning with Imbalanced Datasets
Beyond Unimodal Generalising Neural Processes for Multimodal Uncertainty Estimation
Bias in Evaluation Processes An OptimizationBased Model
Bicriteria Approximation Algorithms for the Submodular Cover Problem
Bicriteria Multidimensional Mechanism Design with Side Information
Bilevel Coreset Selection in Continual Learning A New Formulation and Algorithm
BiLevel Offline Policy Optimization with Limited Exploration
BiMatting Efficient Video Matting via Binarization
Binarized Neural Machine Translation
Binarized Spectral Compressive Imaging
Binary Classification with Confidence Difference
Binary Radiance Fields
BIOT Biosignal Transformer for Crossdata Learning in the Wil
Birder CommunicationEfficient 1bit Adaptive Optimizer for Practical Distributed DNN Training
BIRD Generalizable Backdoor Detection and Removal for Deep Reinforcement Learning
BiSLSSPS Autotune Step Sizes for Stable Bilevel Optimization
Blackbox Backdoor Defense via Zeroshot Image Purification
BlackBox Differential Privacy for Interactive ML
BLIPDiffusion Pretrained Subject Representation for Controllable TexttoImage Generation and Editing
BlockCoordinate Methods and Restarting for Solving ExtensiveForm Games
Blocked Collaborative Bandits Online Collaborative Filtering with PerItem Budget Constraints
BlockState Transformers
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Block_Broyden's_Methods_for_Solving_Nonlinear_Equations.pdf>Block Broyden's Methods for Solving Nonlinear Equations
Block Coordinate PlugandPlay Methods for Blind Inverse Problems
Block LowRank Preconditioner with Shared Basis for Stochastic Optimization
BlurredDilated Method for Adversarial Attacks
Boosting Adversarial Transferability by Achieving Flat Local Maxima
Boosting Learning for LDPC Codes to Improve the ErrorFloor Performance
Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning
Boosting Verification of Deep Reinforcement Learning via PieceWise Linear Decision Neural Networks
Boosting with Tempered Exponential Measures
Bootstrapped Training of ScoreConditioned Generator for Offline Design of Biological Sequences
Bottleneck Structure in Learned Features LowDimension vs Regularity Tradeo
Bounce Reliable HighDimensional Bayesian Optimization for Combinatorial and Mixed Spaces
Boundary Guided LearningFree Semantic Control with Diffusion Models
Bounded rationality in structured density estimation
Bounding the Invertibility of Privacypreserving Instance Encoding using Fisher Information
Bounding training data reconstruction in DPSGD
BQNCO Bisimulation Quotienting for Efficient Neural Combinatorial Optimization
Brainlike Flexible Visual Inference by Harnessing Feedback Feedforward Alignment
Brain Dissection fMRItrained Networks Reveal Spatial Selectivity in the Processing of Natural Images
Brain encoding models based on multimodal transformers can transfer across language and vision
Brant Foundation Model for Intracranial Neural Signal
Breadcrumbs to the Goal Supervised Goal Selection from HumanintheLoop Feedback
Breaking the CommunicationPrivacyAccuracy Tradeoff with fDifferential Privacy
Bridging the Domain Gap SelfSupervised 3D Scene Understanding with Foundation Models
Bringing regularized optimal transport to lightspeed a splitting method adapted for GPUs
Bucks for Buckets B4B Active Defenses Against Stealing Encoders
Budgeting Counterfactual for Offline RL
Bypassing the Simulator NearOptimal Adversarial Linear Contextual Bandits
Bypass Exponential Time Preprocessing Fast Neural Network Training via WeightData Correlation Preprocessing
ByzantineTolerant Methods for Distributed Variational Inequalities
CADet Fully SelfSupervised OutOfDistribution Detection With Contrastive Learning
CalDETR Calibrated Detection Transformer
Calibrate and Boost Logical Expressiveness of GNN Over MultiRelational and Temporal Graphs
Calibrating Cheap Signals in Peer Review without a Prior
Calibrating Neural SimulationBased Inference with Differentiable Coverage Probability
Calibration by Distribution Matching Trainable Kernel Calibration Metrics
CalQL Calibrated Offline RL PreTraining for Efficient Online FineTuning
CAMEL Communicative Agents for Mind Exploration of Large Language Model Society
CamoPatch An Evolutionary Strategy for Generating Camoflauged Adversarial Patches
CaMP Causal Multipolicy Planning for Interactive Navigation in Multiroom Scenes
Canonical normalizing flows for manifold learning
Can Language Models Teach Teacher Explanations Improve Student Performance via Personalization
Can PreTrained TexttoImage Models Generate Visual Goals for Reinforcement Learning
Can You Rely on Your Model Evaluation Improving Model Evaluation with Synthetic Test Data
Cappy Outperforming and Boosting Large MultiTask LMs with a Small Scorer
CAPro Webly Supervised Learning with Crossmodality Aligned Prototypes
CAP CorrelationAware Pruning for HighlyAccurate Sparse Vision Models
CARE Modeling Interacting Dynamics Under Temporal Environmental Variation
Cascading Bandits Optimizing Recommendation Frequency in Delayed Feedback Environments
Cascading Contextual Assortment Bandits
CAST CrossAttention in Space and Time for Video Action Recognition
CategoryExtensible OutofDistribution Detection via Hierarchical Context Descriptions
CATWalk Inductive Hypergraph Learning via Set Walks
Causalstructure Driven Augmentations for Text OOD Generalization
Causal Component Analysis
Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness
Causal de Finetti On the Identification of Invariant Causal Structure in Exchangeable Data
Causal discovery from observational and interventional data across multiple environments
Causal Discovery from Subsampled Time Series with Proxy Variables
Causal Discovery in SemiStationary Time Series
Causal Effect Identification in Uncertain Causal Networks
Causal Effect Regularization Automated Detection and Removal of Spurious Correlations
Causal Fairness for Outcome Control
Causal Imitability Under ContextSpecific Independence Relations
Causal Interpretation of SelfAttention in PreTrained Transformers
CauseEffect Inference in LocationScale Noise Models Maximum Likelihood vs. Independence Testing
Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks
CBD A Certified Backdoor Detector Based on Local Dominant Probability
CDGraB Coordinating Distributed Example Orders for Provably Accelerated Training
CDisentanglement Discovering CausallyIndependent Generative Factors under an Inductive Bias of Confounder
CEIL Generalized Contextual Imitation Learning
CELLE2 Translating Proteins to Pictures and Back with a Bidirectional TexttoImage Transformer
Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback
Certifiably Robust Graph Contrastive Learning
Certification of Distributional Individual Fairness
Certified Minimax Unlearning with Generalization Rates and Deletion Capacity
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Chameleon PlugandPlay Compositional Reasoning with Large Language Models
Chanakya Learning Runtime Decisions for Adaptive RealTime Perception
Change point detection and inference in multivariate nonparametric models under mixing conditions
Characterization and Learning of Causal Graphs with Small Conditioning Sets
Characterization of Overfitting in Robust Multiclass Classification
Characterizing Graph Datasets for Node Classification HomophilyHeterophily Dichotomy and Beyon
Characterizing OutofDistribution Error via Optimal Transport
Characterizing the Impacts of Semisupervised Learning for Weak Supervision
Chasing Fairness Under Distribution Shift A Model Weight Perturbation Approach
ChatGPTPowered Hierarchical Comparisons for Image Classification
Chatting Makes Perfect Chatbased Image Retrieval
Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models
Cheap and Quick Efficient VisionLanguage Instruction Tuning for Large Language Models
Circuit as Set of Points
CLadder A Benchmark to Assess Causal Reasoning Capabilities of Language Models
ClassConditional Conformal Prediction with Many Classes
ClassDistributionAware PseudoLabeling for SemiSupervised MultiLabel Learning
Classification of Heavytailed Features in High Dimensions a Superstatistical Approach
CLeAR Continual Learning on Algorithmic Reasoning for Humanlike Intelligence
CLIP4HOI Towards Adapting CLIP for Practical ZeroShot HOI Detection
CLNeRF Continual Learning of Neural Radiance Fields for Evolving Scene Representation
Closing the ComputationalStatistical Gap in Best Arm Identification for Combinatorial Semibandits
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Closing_the_gap_between_the_upper_bound_and_lower_bound_of_Adam's_iteration_complexity.pdf>Closing the gap between the upper bound and lower bound of Adam's iteration complexity
CluB Cluster Meets BEV for LiDARBased 3D Object Detection
Clusteraware Semisupervised Learning Relational Knowledge Distillation Provably Learns Clustering
ClusterFomer Clustering As A Universal Visual Learner
Clustering the Sketch Dynamic Compression for Embedding Tables
Cocktail Mixing MultiModality Control for TextConditional Image Generation
CoDA Collaborative Novel Box Discovery and Crossmodal Alignment for Openvocabulary 3D Object Detection
CoDet Cooccurrence Guided RegionWord Alignment for OpenVocabulary Object Detection
CoDrug Conformal Drug Property Prediction with Density Estimation under Covariate Shift
Cognitive Model Discovery via Disentangled RNNs
Cognitive Steering in Deep Neural Networks via LongRange Modulatory Feedback Connections
CoLA Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra
Cold Diffusion Inverting Arbitrary Image Transforms Without Noise
Collaboratively Learning Linear Models with Structured Missing Data
Collaborative Alignment of NLP Models
Collaborative Learning via Prediction Consensus
Collaborative Score Distillation for Consistent Visual Editing
Collapsed Inference for Bayesian Deep Learning
CoLLAT On Adding Finegrained Audio Understanding to Language Models using TokenLevel LockedLanguage Tuning
Color Equivariant Convolutional Networks
Combating Bilateral Edge Noise for Robust Link Prediction
Combinatorial Group Testing with Selfish Agents
Combinatorial Optimization with Policy Adaptation using Latent Space Search
Combining Behaviors with the Successor Features Keyboar
CommonScenes Generating Commonsense 3D Indoor Scenes with Scene Graphs
CommunicationEfficient Federated Bilevel Optimization with Global and Local Lower Level Problems
Compact Neural Volumetric Video Representations with Dynamic Codebooks
Comparing Apples to Oranges Learning Similarity Functions for Data Produced by Different Distributions
Comparing Causal Frameworks Potential Outcomes, Structural Models, Graphs, and Abstractions
Complementary Benefits of Contrastive Learning and SelfTraining Under Distribution Shift
Complexity of DerivativeFree Policy Optimization for Structured mathcalH infty Control
Complexvalued Neurons Can Learn More but Slower than Realvalued Neurons via Gradient Descent
Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints
Composable Coresets for Determinant Maximization Greedy is Almost Optimal
Composing ParameterEfficient Modules with Arithmetic Operation
Compositional Abilities Emerge Multiplicatively Exploring Diffusion Models on a Synthetic Task
Compositional Foundation Models for Hierarchical Planning
Compositional Generalization from First Principles
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees
Compositional Sculpting of Iterative Generative Processes
Compressed Video Prompt Tuning
Computational Complexity of Learning Neural Networks Smoothness and Degeneracy
Computational Guarantees for Doubly Entropic Wasserstein Barycenters
Computing Approximate ell p Sensitivities
Computing Optimal Equilibria and Mechanisms via Learning in ZeroSum ExtensiveForm Games
Computing Optimal Nash Equilibria in Multiplayer Games
ComSL A Composite SpeechLanguage Model for EndtoEnd SpeechtoText Translation
Concept Algebra for ScoreBased TextControlled Generative Models
Concept Distillation Leveraging HumanCentered Explanations for Model Improvement
ConDaFormer Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding
Conditional Adapters Parameterefficient Transfer Learning with Fast Inference
Conditional Matrix Flows for Gaussian Graphical Models
Conditional Score Guidance for TextDriven ImagetoImage Translation
Coneheads Hierarchy Aware Attention
Conformalized matrix completion
Conformal PID Control for Time Series Prediction
Conformal Prediction for Time Series with Modern Hopfield Networks
Conformal Prediction for UncertaintyAware Planning with Diffusion Dynamics Model
Connected Superlevel Set in Deep Reinforcement Learning and its Application to Minimax Theorems
Connecting Certified and Adversarial Training
Connecting Multimodal Contrastive Representations
Connecting Pretrained Language Model and Downstream Task via Properties of Representation
ConRad Image Constrained Radiance Fields for 3D Generation from a Single Image
Conservative Offline Policy Adaptation in MultiAgent Games
Conservative State Value Estimation for Offline Reinforcement Learning
Consistent Aggregation of Objectives with Diverse Time Preferences Requires NonMarkovian Rewards
Consistent Diffusion Models Mitigating Sampling Drift by Learning to be Consistent
Constrained Policy Optimization with Explicit Behavior Density For Offline Reinforcement Learning
ConstraintConditioned Policy Optimization for Versatile Safe Reinforcement Learning
Constructing Nonisotropic Gaussian Diffusion Model Using Isotropic Gaussian Diffusion Model for Image Editing
Construction of Hierarchical Neural Architecture Search Spaces based on Contextfree Grammars
Contentbased Unrestricted Adversarial Attack
Contextguided Embedding Adaptation for Effective Topic Modeling in LowResource Regimes
Contextlumpable stochastic bandits
Contextually Affinitive Neighborhood Refinery for Deep Clustering
Contextual Bandits and Imitation Learning with PreferenceBased Active Queries
Contextual Gaussian Process Bandits with Neural Networks
Contextual Stochastic Bilevel Optimization
Context Shift Reduction for Offline MetaReinforcement Learning
ContiFormer ContinuousTime Transformer for Irregular Time Series Modeling
ContinuAR Continuous Autoregression For InfiniteFidelity Fusion
Continuoustime Analysis of Anchor Acceleration
ContinuousTime Functional Diffusion Processes
Continuous Parametric Optical Flow
Contrast, Attend and Diffuse to Decode HighResolution Images from Brain Activities
Contrastive Modules with Temporal Attention for MultiTask Reinforcement Learning
Contrastive Moments Unsupervised Halfspace Learning in Polynomial Time
Contrastive Retrospection honing in on critical steps for rapid learning and generalization in RL
Contrastive Sampling Chains in Diffusion Models
Contrastive Training of ComplexValued Autoencoders for Object Discovery
Contrast Everything A Hierarchical Contrastive Framework for Medical TimeSeries
Controlling TexttoImage Diffusion by Orthogonal Finetuning
Convergence analysis of ODE models for accelerated firstorder methods via positive semidefinite kernels
Convergence Analysis of Sequential Federated Learning on Heterogeneous Data
Convergence of ActorCritic with MultiLayer Neural Networks
Convergent Bregman PlugandPlay Image Restoration for Poisson Inverse Problems
ConvexConcave ZeroSum Stochastic Stackelberg Games
Convolutional Neural Operators for robust and accurate learning of PDEs
Convolutional State Space Models for LongRange Spatiotemporal Modeling
Convolutional Visual Prompt for Robust Visual Perception
Convolutions Die Hard OpenVocabulary Segmentation with Single Frozen Convolutional CLIP
Convolution Monge Mapping Normalization for learning on sleep data
Cookie Consent Has Disparate Impact on Estimation Accuracy
CoPriv NetworkProtocol CoOptimization for CommunicationEfficient Private Inference
Coresets for Fair and Diverse Data Summarization
CORNN Convex optimization of recurrent neural networks for rapid inference of neural dynamics
Correlation Aware Sparsified Mean Estimation Using Random Projection
Correlative Information Maximization A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry
CorresNeRF Image Correspondence Priors for Neural Radiance Fields
CorruptionRobust Offline Reinforcement Learning with General Function Approximation
CosNet A Generalized Spectral Kernel Network
CounterfactualAugmented Importance Sampling for SemiOffline Policy Evaluation
Counterfactually Comparing Abstaining Classifiers
Counterfactually Fair Representation
Counterfactual Conservative Q Learning for Offline Multiagent Reinforcement Learning
Counterfactual Generation with Identifiability Guarantees
Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation
Counting Distinct Elements Under PersonLevel Differential Privacy
Coupled Reconstruction of Cortical Surfaces by Diffeomorphic Mesh Deformation
Covarianceadaptive best arm identification
CPSLAM Collaborative Neural Pointbased SLAM System
CQM Curriculum Reinforcement Learning with a Quantized World Model
Creating a Public Repository for Joining Private Data
Creating MultiLevel Skill Hierarchies in Reinforcement Learning
Credal Marginal MAP
CROMA Remote Sensing Representations with Contrastive RadarOptical Masked Autoencoders
CrossDomain Policy Adaptation via ValueGuided Data Filtering
CrossEpisodic Curriculum for Transformer Agents
CrossGNN Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement
Crosslinks Matter for Link Prediction Rethinking the Debiased GNN from a Data Perspective
Crossmodal Active Complementary Learning with Selfrefining Correspondence
Crossmodal Prompts Adapting Large Pretrained Models for AudioVisual Downstream Tasks
CrossScale MAE A Tale of Multiscale Exploitation in Remote Sensing
CRoSS Diffusion Model Makes Controllable, Robust and Secure Image Steganography
Crystal Structure Prediction by Joint Equivariant Diffusion
CSIsolate Extracting Hard Confident Examples by Content and Style Isolation
CSLPAE A Contrastive SplitLatent Permutation Autoencoder Framework for ZeroShot Electroencephalography Signal Conversion
CSOT Curriculum and StructureAware Optimal Transport for Learning with Noisy Labels
Curriculum Learning for Graph Neural Networks Which Edges Should We Learn First
Curvature Filtrations for Graph Generative Model Evaluation
Curve Your Enthusiasm Concurvity Regularization in Differentiable Generalized Additive Models
Customizable Image Synthesis with Multiple Subjects
CWCL CrossModal Transfer with Continuously Weighted Contrastive Loss
CycleNet Rethinking Cycle Consistency in TextGuided Diffusion for Image Manipulation
D4Explainer Indistribution Explanations of Graph Neural Network via Discrete Denoising Diffusion
DACDETR Divide the Attention Layers and Conquer
DAMEX Datasetaware MixtureofExperts for visual understanding of mixtureofdatasets
DASpeech Directed Acyclic Transformer for Fast and Highquality SpeechtoSpeech Translation
DataCentric Learning from Unlabeled Graphs with Diffusion Model
DataDependent Bounds for Online Portfolio Selection Without Lipschitzness and Smoothness
Datadriven Optimal Filtering for Linear Systems with Unknown Noise Covariances
DataInformed Geometric Space Selection
DaTaSeg Taming a Universal MultiDataset MultiTask Segmentation Model
DatasetDM Synthesizing Data with Perception Annotations Using Diffusion Models
Dataset Diffusion Diffusionbased Synthetic Data Generation for PixelLevel Semantic Segmentation
Data Market Design through Deep Learning
Data Minimization at Inference Time
Data Pruning via MovingoneSampleout
Data Quality in Imitation Learning
Data Selection for Language Models via Importance Resampling
DAW Exploring the Better Weighting Function for Semisupervised Semantic Segmentation
DCIPHER Discovery of Closedform Partial Differential Equations
DDCoT DutyDistinct ChainofThought Prompting for Multimodal Reasoning in Language Models
DDFHO HandHeld Object Reconstruction via Conditional Directed Distance Fiel
Debiased and Denoised Entity Recognition from Distant Supervision
Debiasing Conditional Stochastic Optimization
Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes
Debiasing Scores and Prompts of 2D Diffusion for Viewconsistent Textto3D Generation
Decentralized Matrix Sensing Statistical Guarantees and Fast Convergence
Deciphering SpatioTemporal Graph Forecasting A Causal Lens and Treatment
DecisionAware ActorCritic with Function Approximation and Theoretical Guarantees
Decision Stacks Flexible Reinforcement Learning via Modular Generative Models
Decision Tree for Locally Private Estimation with Public Data
Decompose a Task into Generalizable Subtasks in MultiAgent Reinforcement Learning
Decompose Novel into Known Part Concept Learning For 3D Novel Class Discovery
Deconstructing Data Reconstruction Multiclass, Weight Decay and General Losses
Decorate3D TextDriven HighQuality Texture Generation for Mesh Decoration in the Wil
Deductive Verification of ChainofThought Reasoning
DeepACO Neuralenhanced Ant Systems for Combinatorial Optimization
DeepPCR Parallelizing Sequential Operations in Neural Networks
DeepSimHO Stable Pose Estimation for HandObject Interaction via Physics Simulation
Deep Contract Design via Discontinuous Networks
Deep Equilibrium Based Neural Operators for SteadyState PDEs
Deep Gaussian Markov Random Fields for GraphStructured Dynamical Systems
Deep Insights into Noisy Pseudo Labeling on Graph Data
Deep learning with kernels through RKHM and the PerronFrobenius operator
Deep Nonlineofsight Imaging from Underscanning Measurements
Deep Optimal Transport A Practical Algorithm for Photorealistic Image Restoration
Deep Patch Visual Odometry
Deep Recurrent Optimal Stopping
Deep Stochastic Processes via Functional Markov Transition Operators
Defending against DataFree Model Extraction by Distributionally Robust Defensive Training
Defending Pretrained Language Models as Fewshot Learners against Backdoor Attacks
Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization
DELIFFAS Deformable Light Fields for Fast Avatar Synthesis
DELTA Diverse Client Sampling for Fasting Federated Learning
Demo2Code From Summarizing Demonstrations to Synthesizing Code via Extended ChainofThought
Demographic Parity Constrained Minimax Optimal Regression under Linear Model
Demystifying Structural Disparity in Graph Neural Networks Can One Size Fit All
Demystifying the Optimal Performance of MultiClass Classification
DenseExponential Random Features Sharp Positive Estimators of the Gaussian Kernel
Density of States Prediction of Crystalline Materials via Promptguided MultiModal Transformer
Depthdiscriminative Metric Learning for Monocular 3D Object Detection
Derandomized novelty detection with FDR control via conformal evalues
DesCo Learning Object Recognition with Rich Language Descriptions
Describe, Explain, Plan and Select Interactive Planning with LLMs Enables OpenWorld MultiTask Agents
Described Object Detection Liberating Object Detection with Flexible Expressions
Designing Robust Transformers using Robust Kernel Density Estimation
Design from Policies Conservative TestTime Adaptation for Offline Policy Optimization
DESSERT An Efficient Algorithm for Vector Set Search with Vector Set Queries
Detecting Any HumanObject Interaction Relationship Universal HOI Detector with Spatial Prompt Learning on Foundation Models
Detecting hidden confounding in observational data using multiple environments
Detection Based Partlevel Articulated Object Reconstruction from Single RGBD Image
De novo Drug Design using Reinforcement Learning with Multiple GPT Agents
DFRD DataFree Robustness Distillation for Heterogeneous Federated Learning
DiffAttack Evasion Attacks Against DiffusionBased Adversarial Purification
DiffComplete Diffusionbased Generative 3D Shape Completion
DIFFERDecomposing Individual Reward for Fair Experience Replay in MultiAgent Reinforcement Learning
Differentiable and Stable LongRange Tracking of Multiple Posterior Modes
Differentiable Blocks World Qualitative 3D Decomposition by Rendering Primitives
Differentiable Clustering with Perturbed Spanning Forests
Differentiable NeuroSymbolic Reasoning on LargeScale Knowledge Graphs
Differentiable Random Partition Models
Differentiable Sampling of Categorical Distributions Using the CatLogDerivative Trick
Differentiable sorting for censored timetoevent data
Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection
Differentially Private Statistical Inference through betaDivergence One Posterior Sampling
DiffFoley Synchronized VideotoAudio Synthesis with Latent Diffusion Models
DiffInstruct A Universal Approach for Transferring Knowledge From Pretrained Diffusion Models
<a href=http://doc.flyingfry.cc/NIPS2023/poster/DiffKendall_A_Novel_Approach_for_FewShot_Learning_with_Differentiable_Kendall's_Rank_Correlation.pdf>DiffKendall A Novel Approach for FewShot Learning with Differentiable Kendall's Rank Correlation
DiffPack A Torsional Diffusion Model for Autoregressive Protein SideChain Packing
DiffSketcher Text Guided Vector Sketch Synthesis through Latent Diffusion Models
DiffTraj Generating GPS Trajectory with Diffusion Probabilistic Model
Diffused Redundancy in Pretrained Representations
Diffused TaskAgnostic Milestone Planner
DiffusionBased Adversarial Sample Generation for Improved Stealthiness and Controllability
DiffusionBased Probabilistic Uncertainty Estimation for Active Domain Adaptation
DiffusionSS3D Diffusion Model for Semisupervised 3D Object Detection
Diffusion Hyperfeatures Searching Through Time and Space for Semantic Correspondence
Diffusion Model for Graph Inverse Problems Towards Effective Source Localization on Complex Networks
Diffusion Model is an Effective Planner and Data Synthesizer for MultiTask Reinforcement Learning
Diffusion Probabilistic Models for Structured Node Classification
Diffusion Representation for Asymmetric Kernels via Magnetic Transform
Diffusion SelfGuidance for Controllable Image Generation
DiffUTE Universal Text Editing Diffusion Model
DiffVL Scaling Up Soft Body Manipulation using VisionLanguage Driven Differentiable Physics
DinoSR SelfDistillation and Online Clustering for Selfsupervised Speech Representation Learning
DINSQL Decomposed InContext Learning of TexttoSQL with SelfCorrection
Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data
Directional diffusion models for graph representation learning
Directionoriented Multiobjective Learning Simple and Provable Stochastic Algorithms
Direct Diffusion Bridge using Data Consistency for Inverse Problems
Direct Preferencebased Policy Optimization without Reward Modeling
Direct Training of SNN using Local Zeroth Order Metho
Disambiguated Attention Embedding for MultiInstance PartialLabel Learning
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning
Discovering Intrinsic SpatialTemporal Logic Rules to Explain Human Actions
Discover and Align Taxonomic Context Priors for Openworld SemiSupervised Learning
DISCOVER Making Vision Networks Interpretable via Competition and Dissection
DiscreteSmoothness in Online Algorithms with Predictions
Discriminative Calibration Check Bayesian Computation from Simulations and Flexible Classifier
Discriminative Feature Attributions Bridging Post Hoc Explainability and Inherent Interpretability
DisDiff Unsupervised Disentanglement of Diffusion Probabilistic Models
Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning
Disentangled Wasserstein Autoencoder for TCell Receptor Engineering
Disentanglement via Latent Quantization
Disentangling Cognitive Diagnosis with Limited Exercise Labels
Disentangling Voice and Content with SelfSupervision for Speaker Recognition
Disinhibitory neuronal circuits can control the sign of synaptic plasticity
Dissecting ChainofThought Compositionality through InContext Filtering and Learning
Distilling OutofDistribution Robustness from VisionLanguage Foundation Models
Distributed Inference and Finetuning of Large Language Models Over The Internet
Distributed Personalized Empirical Risk Minimization
Distributionally Robust Bayesian Optimization with varphidivergences
Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training
Distributional Learning of Variational AutoEncoder Application to Synthetic Data Generation
Distributional Model Equivalence for RiskSensitive Reinforcement Learning
Distributional ParetoOptimal MultiObjective Reinforcement Learning
Distributional Policy Evaluation a Maximum Entropy approach to Representation Learning
DistributionFree ModelAgnostic Regression Calibration via Nonparametric Methods
Distribution Learnability and Robustness
DiT3D Exploring Plain Diffusion Transformers for 3D Shape Generation
Diverse Conventions for HumanAI Collaboration
Diverse Shape Completion via Style Modulated Generative Adversarial Networks
Diversified Outlier Exposure for OutofDistribution Detection via Informative Extrapolation
Diversifying SpatialTemporal Perception for Video Domain Generalization
Diversify & Conquer Outcomedirected Curriculum RL via OutofDistribution Disagreement
Diversify Your Vision Datasets with Automatic Diffusionbased Augmentation
Divide, Evaluate, and Refine Evaluating and Improving TexttoImage Alignment with Iterative VQA Feedback
DiViNeT 3D Reconstruction from Disparate Views using Neural Template Regularization
Django Detecting Trojans in Object Detection Models via Gaussian Focus Calibration
Does a sparse ReLU network training problem always admit an optimum
Does Graph Distillation See Like Vision Dataset Counterpart
Does Invariant Graph Learning via Environment Augmentation Learn Invariance
Does Visual Pretraining Help EndtoEnd Reasoning
Domain Adaptive Imitation Learning with Visual Observation
Domain Agnostic Fourier Neural Operators
Domain ReModulation for FewShot Generative Domain Adaptation
Domain Watermark Effective and Harmless Dataset Copyright Protection is Closed at Han
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Don't_be_so_Monotone_Relaxing_Stochastic_Line_Search_in_OverParameterized_Models.pdf>Don't be so Monotone Relaxing Stochastic Line Search in OverParameterized Models
Dont blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy
Dont just prune by magnitude! Your mask topology is a secret weapon
Dont Stop Pretraining Make Promptbased Finetuning Powerful Learner
DOSE Diffusion Dropout with Adaptive Prior for Speech Enhancement
Double and Single Descent in Causal Inference with an Application to HighDimensional Synthetic Control
Double Auctions with Twosided Bandit Feedback
Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning Generic Algorithm and Robust Partial Coverage
Double Randomized Underdamped Langevin with DimensionIndependent Convergence Guarantee
DoublyRobust SelfTraining
Doubly Constrained Fair Clustering
Doubly Robust Augmented Transfer for MetaReinforcement Learning
DoWG Unleashed An Efficient Universal ParameterFree Gradient Descent Metho
Do Not Marginalize Mechanisms, Rather Consolidate!
Do SSL Models Have Dja Vu A Case of Unintended Memorization in Selfsupervised Learning
DPHyPO An Adaptive Private Framework for Hyperparameter Optimization
DPMix Mixupbased Data Augmentation for Differentially Private Learning
DPMSolverv3 Improved Diffusion ODE Solver with Empirical Model Statistics
DRAUC An Instancewise Distributionally Robust AUC Optimization Framework
DreamSparse Escaping from Platos Cave with 2D Diffusion Model Given Sparse Views
DreamWaltz Make a Scene with Complex 3D Animatable Avatars
Dream the Impossible Outlier Imagination with Diffusion Models
DRF Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Drift_doesn't_Matter_Dynamic_Decomposition_with_Diffusion_Reconstruction_for_Unstable_Multivariate_Time_Series_Anomaly_Detection.pdf>Drift doesn't Matter Dynamic Decomposition with Diffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection
DropCompute simple and more robust distributed synchronous training via compute variance reduction
DropPos PreTraining Vision Transformers by Reconstructing Dropped Positions
DrugCLIP Contrasive ProteinMolecule Representation Learning for Virtual Screening
DSeparation for Causal SelfExplanation
DSR Dynamical Surface Representation as Implicit Neural Networks for Protein
Dual MeanTeacher An Unbiased SemiSupervised Framework for AudioVisual Source Localization
Dual SelfAwareness Value Decomposition Framework without Individual Global Max for Cooperative MARL
DYffusion A Dynamicsinformed Diffusion Model for Spatiotemporal Forecasting
Dynamically Masked Discriminator for GANs
Dynamics Generalisation in Reinforcement Learning via Adaptive ContextAware Policies
Dynamic Nonmonotone Submodular Maximization
Dynamic Personalized Federated Learning with Adaptive Differential Privacy
Dynamic Pricing and Learning with Bayesian Persuasion
Dynamic Prompt Learning Addressing CrossAttention Leakage for TextBased Image Editing
Dynamic Regret of Adversarial Linear Mixture MDPs
Dynamic Sparsity Is ChannelLevel Sparsity Learner
DynamoDepth Fixing Unsupervised Depth Estimation for Dynamical Scenes
DynGFN Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets
DynPoint Dynamic Neural Point For View Synthesis
D^2CSG Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts
E2PNet Event to Point Cloud Registration with SpatioTemporal Representation Learning
Easy Learning from Label Proportions
Echoes Beyond Points Unleashing the Power of Raw Radar Data in Multimodality Fusion
Ecosystemlevel Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
EDGI Equivariant Diffusion for Planning with Embodied Agents
Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
Effective Bayesian Heteroscedastic Regression with Deep Neural Networks
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data
Effective Targeted Attacks for Adversarial SelfSupervised Learning
Efficiently incorporating quintuple interactions into geometric deep learning force fields
Efficient Activation Function Optimization through Surrogate Modeling
Efficient Adaptation of Large Vision Transformer via Adapter ReComposing
Efficient Adversarial Attacks on Online Multiagent Reinforcement Learning
Efficient Algorithms for Generalized Linear Bandits with Heavytailed Rewards
Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination
Efficient Bayesian Learning Curve Extrapolation using PriorData Fitted Networks
Efficient Beam Tree Recursion
Efficient Data Subset Selection to Generalize Training Across Models Transductive and Inductive Networks
Efficient Diffusion Policies For Offline Reinforcement Learning
Efficient Equivariant Transfer Learning from Pretrained Models
Efficient Exploration in Continuoustime Modelbased Reinforcement Learning
Efficient Hyperparameter Optimization with Cubic Regularization
Efficient Learning of Linear Graph Neural Networks via Node Subsampling
Efficient Lowrank Backpropagation for Vision Transformer Adaptation
Efficient Meta Neural Heuristic for MultiObjective Combinatorial Optimization
Efficient ModelFree Exploration in LowRank MDPs
Efficient Neural Music Generation
Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents
Efficient Potentialbased Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric
Efficient RL with Impaired Observability Learning to Act with Delayed and Missing State Observations
Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs
Efficient Sampling of Stochastic Differential Equations with Positive SemiDefinite Models
Efficient Subgame Refinement for Extensiveform Games
Efficient Symbolic Policy Learning with Differentiable Symbolic Expression
Efficient Testable Learning of Halfspaces with Adversarial Label Noise
Efficient TestTime Adaptation for SuperResolution with SecondOrder Degradation and Reconstruction
Efficient Training of EnergyBased Models Using Jarzynski Equality
Efficient Uncertainty Quantification and Reduction for OverParameterized Neural Networks
Egocentric Planning for Scalable Embodied Task Achievement
EgoDistill Egocentric Head Motion Distillation for Efficient Video Understanding
EICIL Joint Excitatory Inhibitory Cycle Iteration Learning for Deep Spiking Neural Networks
Elastic Decision Transformer
ELDEN Exploration via Local Dependencies
Eliciting User Preferences for Personalized MultiObjective Decision Making through Comparative Feedback
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization
Eliminating Domain Bias for Federated Learning in Representation Space
Embedding Space Interpolation Beyond MiniBatch, Beyond Pairs and Beyond Examples
Embracing the chaos analysis and diagnosis of numerical instability in variational flows
Embroid Unsupervised Prediction Smoothing Can Improve FewShot Classification
Emergent and Predictable Memorization in Large Language Models
Emergent Communication for Rules Reasoning
Emergent Communication in Interactive Sketch Question Answering
Emergent Correspondence from Image Diffusion
EMMAX An EMlike Multilingual Pretraining Algorithm for Crosslingual Representation Learning
Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss
Empowering Convolutional Neural Nets with MetaSin Activation
Encoding Human Behavior in Information Design through Deep Learning
EndToEnd Latent Variational Diffusion Models for Inverse Problems in High Energy Physics
EndtoEnd MetaBayesian Optimisation with Transformer Neural Processes
EnergyBased Cross Attention for Bayesian Context Update in TexttoImage Diffusion Models
Energybased learning algorithms for analog computing a comparative study
EnergyBased Models for Anomaly Detection A Manifold Diffusion Recovery Approach
EnergyBased Sliced Wasserstein Distance
EnergyEfficient Scheduling with Predictions
Energy Discrepancies A ScoreIndependent Loss for EnergyBased Models
Energy Guided Diffusion for Generating Neurally Exciting Images
Energy Transformer
Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization
Enhancing Adversarial Robustness via ScoreBased Optimization
Enhancing CLIP with CLIP Exploring Pseudolabeling for LimitedLabel Prompt Tuning
Enhancing Knowledge Transfer for Task Incremental Learning with Datafree Subnetwork
Enhancing Minority Classes by Mixing An Adaptative Optimal Transport Approach for Longtailed Classification
Enhancing Motion Deblurring in HighSpeed Scenes with Spike Streams
Enhancing Robot Program Synthesis Through Environmental Context
Enhancing SharpnessAware Optimization Through Variance Suppression
Enhancing User Intent Capture in SessionBased Recommendation with Attribute Patterns
Ensemblebased Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift
Entropybased Training Methods for Scalable Neural Implicit Samplers
Entropydissipation Informed Neural Network for McKeanVlasov Type PDEs
EnvironmentAware Dynamic Graph Learning for OutofDistribution Generalization
Epidemic Learning Boosting Decentralized Learning with Randomized Communication
Equal Opportunity of Coverage in Fair Regression
Equivariant Adaptation of Large Pretrained Models
Equivariant flow matching
Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics
Equivariant Single View Pose Prediction Via Induced and Restriction Representations
Equivariant SpatioTemporal Attentive Graph Networks to Simulate Physical Dynamics
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Errorsinvariables_Fr'echet_Regression_with_Lowrank_Covariate_Approximation.pdf>Errorsinvariables Fr'echet Regression with Lowrank Covariate Approximation
Error Discovery By Clustering Influence Embeddings
ESSEN Improving Evolution State Estimation for Temporal Networks using Von Neumann Entropy
EssInfoGAIL Semisupervised Imitation Learning from Imbalanced Demonstrations
Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors
Estimating Causal Effects Identifiable from a Combination of Observations and Experiments
Estimating Koopman operators with sketching to provably learn large scale dynamical systems
Estimating Noise Correlations Across Continuous Conditions With Wishart Processes
Estimating Propensity for Causalitybased Recommendation without Exposure Data
Estimating Riemannian Metric with NoiseContaminated Intrinsic Distance
Estimating the RateDistortion Function by Wasserstein Gradient Descent
Evaluating Cognitive Maps and Planning in Large Language Models with CogEval
Evaluating Neuron Interpretation Methods of NLP Models
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance
Every Parameter Matters Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
EvoFed Leveraging Evolutionary Strategies for CommunicationEfficient Federated Learning
Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing
Evolving Connectivity for Recurrent Spiking Neural Networks
Evolving Standardization for Continual Domain Generalization over Temporal Drift
EvoPrompting Language Models for CodeLevel Neural Architecture Search
Exact Generalization Guarantees for Regularized Wasserstein Distributionally Robust Models
Exact Optimality of CommunicationPrivacyUtility Tradeoffs in Distributed Mean Estimation
Exact recovery and Bregman hard clustering of nodeattributed Stochastic Block Model
Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings
Exact Verification of ReLU Neural Control Barrier Functions
Expanding SmallScale Datasets with Guided Imagination
Experimental Designs for Heteroskedastic Variance
Experiment Planning with Function Approximation
Expert load matters operating networks at high accuracy and low manual effort
Explainable and Efficient Randomized Voting Rules
Explainable Brain Age Prediction using coVariance Neural Networks
Explaining Predictive Uncertainty with Information Theoretic Shapley Values
Explaining V1 Properties with a Biologically Constrained Deep Learning Architecture
Explain Any Concept Segment Anything Meets ConceptBased Explanation
Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models
Exploiting Contextual Objects and Relations for 3D Visual Grounding
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits
Exploiting hidden structures in nonconvex games for convergence to Nash equilibrium
Explore to Generalize in ZeroShot RL
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models
Exploring Diverse InContext Configurations for Image Captioning
Exploring Question Decomposition for ZeroShot VQA
Exploring the Optimal Choice for Generative Processes in Diffusion Models Ordinary vs Stochastic Differential Equations
Exponentially Convergent Algorithms for Supervised Matrix Factorization
Exponential Lower Bounds for Fictitious Play in Potential Games
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
Expressive probabilistic sampling in recurrent neural networks
ExpressivityPreserving GNN Simulation
ExPT Synthetic Pretraining for FewShot Experimental Design
Extending the Design Space of Graph Neural Networks by Rethinking Folklore WeisfeilerLehman
Extensible Prompts for Language Models on Zeroshot Language Style Customization
Extracting Reward Functions from Diffusion Models
Extremal Domain Translation with Neural Optimal Transport
FABind Fast and Accurate ProteinLigand Binding
FaceComposer A Unified Model for Versatile Facial Content Creation
FaceDNeRF SemanticsDriven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models
FACE Evaluating Natural Language Generation with Fourier Analysis of CrossEntropy
Face Reconstruction from Facial Templates by Learning Latent Space of a Generator Network
Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes
Facing Off World Model Backbones RNNs, Transformers, and S4
Factorized Contrastive Learning Going Beyond Multiview Redundancy
FailureAware Gaussian Process Optimization with Regret Bounds
Fair, PolylogApproximate LowCost Hierarchical Clustering
FairLISA Fair User Modeling with Limited Sensitive Attributes Information
Fairly Recommending with Social Attributes A Flexible and Controllable Optimization Approach
Fairnessguided Fewshot Prompting for Large Language Models
Fairness Aware Counterfactuals for Subgroups
Fairness Continual Learning Approach to Semantic Scene Understanding in OpenWorld Environments
Fair Adaptive Experiments
Fair Allocation of Indivisible Chores Beyond Additive Costs
Fair Canonical Correlation Analysis
Fair Graph Distillation
Fair Streaming Principal Component Analysis Statistical and Algorithmic Viewpoint
False Discovery Proportion control for aggregated Knockoffs
FAMO Fast Adaptive Multitask Optimization
Fantastic Robustness Measures The Secrets of Robust Generalization
Fantastic Weights and How to Find Them Where to Prune in Dynamic Sparse Training
Faster approximate subgraph counts with privacy
Faster Differentially Private Convex Optimization via SecondOrder Methods
Faster Discrete Convex Function Minimization with Predictions The MConvex Case
Faster Query Times for Fully Dynamic kCenter Clustering with Outliers
Faster Relative Entropy Coding with Greedy Rejection Coding
Fast and Regret Optimal Best Arm Identification Fundamental Limits and LowComplexity Algorithms
Fast and Simple Spectral Clustering in Theory and Practice
Fast Asymptotically Optimal Algorithms for NonParametric Stochastic Bandits
Fast Attention Over Long Sequences With Dynamic Sparse Flash Attention
Fast Attention Requires Bounded Entries
FAST a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation
Fast Bellman Updates for Wasserstein Distributionally Robust MDPs
Fast Conditional Mixing of MCMC Algorithms for Nonlogconcave Distributions
Fast Exact Leverage Score Sampling from KhatriRao Products with Applications to Tensor Decomposition
Fast Model DeBias with Machine Unlearning
Fast Optimal Locally Private Mean Estimation via Random Projections
Fast Partitioned Learned Bloom Filter
Fast Projected Newtonlike Method for Precision Matrix Estimation under Total Positivity
Fast Rank1 Lattice Targeted Sampling for Blackbox Optimization
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow Shrink Trees
Fast Trainable Projection for Robust Finetuning
FDAlign Feature Discrimination Alignment for Finetuning PreTrained Models in FewShot Learning
FeatureLearning Networks Are Consistent Across Widths At Realistic Scales
Feature Dropout Revisiting the Role of Augmentations in Contrastive Learning
Feature Learning for Interpretable, Performant Decision Trees
Feature learning via meanfield Langevin dynamics classifying sparse parities and beyon
Feature Likelihood Score Evaluating the Generalization of Generative Models Using Samples
Feature Selection in the Contrastive Analysis Setting
FeCAM Exploiting the Heterogeneity of Class Distributions in ExemplarFree Continual Learning
FedCO 2 Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning
Federated Compositional Deep AUC Maximization
Federated Conditional Stochastic Optimization
Federated Learning via MetaVariational Dropout
Federated Learning with Bilateral Curation for Partially ClassDisjoint Data
Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness A New Algorithm and Lower Bounds
Federated Learning with Manifold Regularization and Normalized Update Reaggregation
Federated Linear Bandits with Finite Adversarial Actions
Federated MultiObjective Learning
Federated Spectral Clustering via Secure Similarity Reconstruction
FedFA Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense
FedFed Feature Distillation against Data Heterogeneity in Federated Learning
FedGame A GameTheoretic Defense against Backdoor Attacks in Federated Learning
FedGCN ConvergenceCommunication Tradeoffs in Federated Training of Graph Convolutional Networks
FedGraB Federated Longtailed Learning with SelfAdjusting Gradient Balancer
FedL2P Federated Learning to Personalize
FedNAR Federated Optimization with Normalized Annealing Regularization
FewShot ClassIncremental Learning via TrainingFree Prototype Calibration
Fewshot Generation via Recalling BrainInspired EpisodicSemantic Memory
FGPrompt Finegrained Goal Prompting for Imagegoal Navigation
FiGURe Simple and Efficient Unsupervised Node Representations with Filter Augmentations
Finding Counterfactually Optimal Action Sequences in Continuous State Spaces
Finding Local Minima Efficiently in Decentralized Optimization
Finding Order in Chaos A Novel Data Augmentation Method for Time Series in Contrastive Learning
Finding Safe Zones of Markov Decision Processes Policies
Find What You Want Learning Demandconditioned Object Attribute Space for Demanddriven Navigation
FineGrained CrossView GeoLocalization Using a CorrelationAware Homography Estimator
Finegrained Expressivity of Graph Neural Networks
Finegrained Lateinteraction Multimodal Retrieval for Retrieval Augmented Visual Question Answering
FineGrained Theoretical Analysis of Federated ZerothOrder Optimization
FineGrained Visual Prompting
FineMoGen FineGrained SpatioTemporal Motion Generation and Editing
FiniteTime Analysis of SingleTimescale ActorCritic
FiniteTime Analysis of Whittle Index based QLearning for Restless MultiArmed Bandits with Neural Network Function Approximation
Finite Population Regression Adjustment and Nonasymptotic Guarantees for Treatment Effect Estimation
FIRAL An Active Learning Algorithm for Multinomial Logistic Regression
First and SecondOrder Bounds for Adversarial Linear Contextual Bandits
First Order Methods with Markovian Noise from Acceleration to Variational Inequalities
First Order Stochastic Optimization with Oblivious Noise
Fitting trees to ell 1hyperbolic distances
Fixing the NTK From Neural Network Linearizations to Exact Convex Programs
FlatMatch Bridging Labeled Data and Unlabeled Data with CrossSharpness for SemiSupervised Learning
Flat Seeking Bayesian Neural Networks
Flexible AttentionBased MultiPolicy Fusion for Efficient Deep Reinforcement Learning
Flocks of Stochastic Parrots Differentially Private Prompt Learning for Large Language Models
FlowAttentionbased SpatioTemporal Aggregation Network for 3D Mask Detection
FlowBased Feature Fusion for VehicleInfrastructure Cooperative 3D Object Detection
FlowCam Training Generalizable 3D Radiance Fields without Camera Poses via PixelAligned Scene Flow
FlowPG Actionconstrained Policy Gradient with Normalizing Flows
Flow Factorized Representation Learning
Flow Matching for Scalable SimulationBased Inference
Flow Perinstance Personalized Federated Learning
FLSL Featurelevel Selfsupervised Learning
FLuID Mitigating Stragglers in Federated Learning using Invariant Dropout
FOCAL Contrastive Learning for Multimodal TimeSeries Sensing Signals in Factorized Orthogonal Latent Space
Focused Transformer Contrastive Training for Context Scaling
Focus on Query Adversarial Mining Transformer for FewShot Segmentation
Focus Your Attention when FewShot Classification
ForecastPFN SyntheticallyTrained ZeroShot Forecasting
ForkMerge Mitigating Negative Transfer in AuxiliaryTask Learning
Formalizing locality for normative synaptic plasticity models
Formulating Discrete Probability Flow Through Optimal Transport
Foundation Model is Efficient Multimodal Multitask Model Selector
FouriDown Factoring DownSampling into Shuffling and Superposing
FourierGNN Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
FourierHandFlow Neural 4D Hand Representation Using Fourier Query Flow
fPolicy Gradients A General Framework for GoalConditioned RL using fDivergences
Fractal Landscapes in Policy Optimization
Fragmentbased Pretraining and Finetuning on Molecular Graphs
FreeBloom ZeroShot TexttoVideo Generator with LLM Director and LDM Animator
FreeMask Synthetic Images with Dense Annotations Make Stronger Segmentation Models
Frequencydomain MLPs are More Effective Learners in Time Series Forecasting
FrequencyEnhanced Data Augmentation for VisionandLanguage Navigation
Frequency DomainBased Dataset Distillation
From Cloze to Comprehension Retrofitting Pretrained Masked Language Models to Pretrained Machine Reader
From Discrete Tokens to HighFidelity Audio Using MultiBand Diffusion
From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization
From Trainable Negative Depth to Edge Heterophily in Graphs
From ViT Features to Trainingfree Video Object Segmentation via Streamingdata Mixture Models
Frontdoor Adjustment Beyond Markov Equivalence with Limited Graph Knowledge
Fully Dynamic kClustering in tilde Ok Update Time
FunctionalGroupBased Diffusion for PocketSpecific Molecule Generation and Elaboration
Functional Equivalence and Path Connectivity of Reducible Hyperbolic Tangent Networks
Functional Renyi Differential Privacy for Generative Modeling
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks
Fused GromovWasserstein Graph Mixup for Graphlevel Classifications
GacsKorner Common Information Variational Autoencoder
GAIA Delving into Gradientbased Attribution Abnormality for Outofdistribution Detection
GALOPA Graph Transport Learning with Optimal Plan Alignment
Game Solving with Online FineTuning
GAN You See Me Enhanced Data Reconstruction Attacks against Split Inference
GAUCHE A Library for Gaussian Processes in Chemistry
Gaussian Differential Privacy on Riemannian Manifolds
Gaussian Membership Inference Privacy
Gaussian Mixture Solvers for Diffusion Models
Gaussian Process Probes GPP for UncertaintyAware Probing
Generalised fMean Aggregation for Graph Neural Networks
Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations
Generalizable Oneshot 3D Neural Head Avatar
Generalization bounds for neural ordinary differential equations and deep residual networks
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation
Generalized Belief Transport
Generalized equivalences between subsampling and ridge regularization
Generalized Informationtheoretic Multiview Clustering
Generalized Logit Adjustment Calibrating Finetuned Models by Removing Label Bias in Foundation Models
Generalized SemiSupervised Learning via SelfSupervised Feature Adaptation
Generalized test utilities for longtail performance in extreme multilabel classification
Generalized Weighted Path Consistency for Mastering Atari Games
General Munchausen Reinforcement Learning with Tsallis KullbackLeibler Divergence
Generate What You Prefer Reshaping Sequential Recommendation via Guided Diffusion
Generating Behaviorally Diverse Policies with Latent Diffusion Models
Generating Images with Multimodal Language Models
Generative Categorylevel Object Pose Estimation via Diffusion Models
Generative Modeling through the Semidual Formulation of Unbalanced Optimal Transport
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning
Generative Neural Fields by Mixtures of Neural Implicit Functions
Generator Born from Classifier
Generator Identification for Linear SDEs with Additive and Multiplicative Noise
GenS Generalizable Neural Surface Reconstruction from MultiView Images
GeoCLIP ClipInspired Alignment between Locations and Images for Effective Worldwide Geolocalization
Geodesic MultiModal Mixup for Robust FineTuning
Geometric Algebra Transformer
Geometric Analysis of Matrix Sensing over Graphs
Geometric Neural Diffusion Processes
Geometric Transformer with Interatomic Positional Encoding
GeometryAware Adaptation for Pretrained Models
GeometryInformed Neural Operator for LargeScale 3D PDEs
GeoPhy Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies
GeoTMI Predicting Quantum Chemical Property with EasytoObtain Geometry via Positional Denoising
GEQ Gaussian Kernel Inspired Equilibrium Models
Getting ViT in Shape Scaling Laws for ComputeOptimal Model Design
GEX A flexible method for approximating influence via Geometric Ensemble
GIMLET A Unified GraphText Model for InstructionBased Molecule ZeroShot Learning
Glance and Focus Memory Prompting for MultiEvent Video Question Answering
Globalcorrelated 3Ddecoupling Transformer for Clothed Avatar Reconstruction
Globally injective and bijective neural operators
Globally solving the GromovWasserstein problem for point clouds in low dimensional Euclidean spaces
Global Convergence Analysis of Local SGD for Twolayer Neural Network without Overparameterization
Global Identifiability of ell 1based Dictionary Learning via Matrix Volume Optimization
Global Optimality in Bivariate Gradientbased DAG Learning
Global StructureAware Diffusion Process for Lowlight Image Enhancement
Global Update Tracking A Decentralized Learning Algorithm for Heterogeneous Data
GLOBER Coherent Nonautoregressive Video Generation via GLOBal Guided Video DecodER
GlucoSynth Generating DifferentiallyPrivate Synthetic Glucose Traces
GlyphControl Glyph Conditional Control for Visual Text Generation
GMSF Global Matching Scene Flow
GNeSF Generalizable Neural Semantic Fields
GNNEvaluator Evaluating GNN Performance On Unseen Graphs Without Labels
Goalconditioned Offline Planning from Curious Exploration
GoalConditioned Predictive Coding for Offline Reinforcement Learning
Goal Driven Discovery of Distributional Differences via Language Descriptions
Going Beyond Linear Mode Connectivity The Layerwise Linear Feature Connectivity
GoldYOLO Efficient Object Detector via GatherandDistribute Mechanism
GPEX, A Framework For Interpreting Artificial Neural Networks
GPT4Tools Teaching Large Language Model to Use Tools via Selfinstruction
GPTST Generative PreTraining of SpatioTemporal Graph Neural Networks
GradientBased Feature Learning under Structured Data
GradientFree Kernel Stein Discrepancy
Gradient Descent with Linearly Correlated Noise Theory and Applications to Differential Privacy
Gradient Flossing Improving Gradient Descent through Dynamic Control of Jacobians
Gradient Informed Proximal Policy Optimization
GradOrth A Simple yet Efficient OutofDistribution Detection with Orthogonal Projection of Gradients
Grammar Prompting for DomainSpecific Language Generation with Large Language Models
GRANDSLAMIN Interpretable Additive Modeling with Structural Constraints
Granger Components Analysis Unsupervised learning of latent temporal dependencies
GraphAdapter Tuning VisionLanguage Models With Dual Knowledge Graph
GraphMP Graph Neural Networkbased Motion Planning with Efficient Graph Search
GraphPatcher Mitigating Degree Bias for Graph Neural Networks via Testtime Augmentation
GraphStructured Gaussian Processes for Transferable Graph Learning
Graph Contrastive Learning with Stable and Scalable Spectral Encoding
Graph Convolutional Kernel Machine versus Graph Convolutional Networks
Graph Denoising Diffusion for Inverse Protein Folding
Graph Mixture of Experts Learning on LargeScale Graphs with Explicit Diversity Modeling
Graph of Circuits with GNN for Exploring the Optimal Design Space
Grassmann Manifold Flows for Stable Shape Generation
Greatness in Simplicity Unified SelfCycle Consistency for ParserFree Virtual TryOn
Greedy Poisson Rejection Sampling
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing
Grounded Decoding Guiding Text Generation with Grounded Models for Embodied Agents
Group Robust Classification Without Any Group Information
Guarantees for SelfPlay in Multiplayer Games via Polymatrix Decomposability
Guide Your Agent with Adaptive Multimodal Rewards
Guiding Large Language Models via Directional Stimulus Prompting
Guiding The Last Layer in Federated Learning with PreTrained Models
GUST Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence
H2O HeavyHitter Oracle for Efficient Generative Inference of Large Language Models
H2RBoxv2 Incorporating Symmetry for Boosting Horizontal Box Supervised Oriented Object Detection
H3T Efficient Integration of Memory Optimization and Parallelism for Largescale Transformer Training
Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition
HAP StructureAware Masked Image Modeling for HumanCentric Perception
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products
Hardware Resilience Properties of TextGuided Image Classifiers
Hard Prompts Made Easy GradientBased Discrete Optimization for Prompt Tuning and Discovery
Harnessing Hard Mixed Samples with Decoupled Regularizer
Harnessing the power of choices in decision tree learning
HASSOD Hierarchical Adaptive SelfSupervised Object Detection
Have it your way Individualized Privacy Assignment for DPSGD
HConsistency Bounds Characterization and Extensions
HeadSculpt Crafting 3D Head Avatars with Text
HEDNet A Hierarchical EncoderDecoder Network for 3D Object Detection in Point Clouds
HiBug On HumanInterpretable Model Debug
Hidden Poison Machine Unlearning Enables Camouflaged Poisoning Attacks
Hierarchical Adaptive Value Estimation for Multimodal Visual Reinforcement Learning
Hierarchical Gaussian Mixture based Task Generative Model for Robust MetaLearning
Hierarchical MultiAgent Skill Discovery
Hierarchical Openvocabulary Universal Image Segmentation
Hierarchical Randomized Smoothing
Hierarchical SemiImplicit Variational Inference with Application to Diffusion Model Acceleration
Hierarchical VAEs provide a normative account of motion processing in the primate brain
Hierarchical Vector Quantized Transformer for Multiclass Unsupervised Anomaly Detection
Highdimensional Contextual Bandit Problem without Sparsity
HigherOrder Uncoupled Dynamics Do Not Lead to Nash Equilibrium Except When They Do
High dimensional, tabular deep learning with an auxiliary knowledge graph
High Precision Causal Model Evaluation with Conditional Randomization
HInDex Visual Reinforcement Learning with HandInformed Representations for Dexterous Manipulation
HiNeRV Video Compression with Hierarchical Encodingbased Neural Representation
History Filtering in Imperfect Information Games Algorithms and Complexity
Hnobs Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets
Holistic Transfer Towards NonDisruptive FineTuning with Partial Target Data
Homotopybased training of NeuralODEs for accurate dynamics discovery
Horospherical Decision Boundaries for Large Margin Classification in Hyperbolic Space
HotBEV Hardwareoriented Transformerbased MultiView 3D Detector for BEV Perception
How2comm CommunicationEfficient and CollaborationPragmatic MultiAgent Perception
How a Student becomes a Teacher learning and forgetting through Spectral methods
How Does Adaptive Optimization Impact Local Neural Network Geometry
How does GPT2 compute greaterthan Interpreting mathematical abilities in a pretrained language model
How do MinimumNorm Shallow Denoisers Look in Function Space
How many samples are needed to leverage smoothness
How Resampling Helps for LongTail Learning
How to Finetune the Model Unified Model Shift and Model Bias Policy Optimization
How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget
HQAAttack Toward High Quality BlackBox HardLabel Adversarial Attack on Text
HubRouter Learning Global Routing via Hub Generation and Pinhub Connection
HuggingGPT Solving AI Tasks with ChatGPT and its Friends in Hugging Face
HumanAligned Calibration for AIAssisted Decision Making
HumanGuided ComplexityControlled Abstractions
HumanintheLoop Optimization for Deep Stimulus Encoding in Visual Prostheses
Human spatiotemporal pattern learning as probabilistic program synthesis
Hybrid Policy Optimization from Imperfect Demonstrations
Hybrid Search for Efficient Planning with Completeness Guarantees
Hyperbolic Graph Neural Networks at Scale A Meta Learning Approach
Hyperbolic Space with Hierarchical Margin Boosts FineGrained Learning from Coarse Labels
Hyperbolic VAE via Latent Gaussian Distributions
HyperHMM aligning human brains and semantic features in a common latent event space
Hypervolume Maximization A Geometric View of Pareto Set Learning
HyPNeRF Learning Improved NeRF Priors using a HyperNetwork
Hypothesis Selection with Memory Constraints
IBA Towards Irreversible Backdoor Attacks in Federated Learning
IDEA An Invariant Perspective for Efficient Domain Adaptive Image Retrieval
Idempotent Learned Image Compression with RightInverse
Identifiability Guarantees for Causal Disentanglement from Soft Interventions
Identifiable Contrastive Learning with Automatic Feature Importance Discovery
Identification of Nonlinear Latent Hierarchical Models
IDRNet InterventionDriven Relation Network for Semantic Segmentation
IEBins Iterative Elastic Bins for Monocular Depth Estimation
Ignorance is Bliss Robust Control via Information Gating
ImageBrush Learning Visual InContext Instructions for ExemplarBased Image Manipulation
ImageReward Learning and Evaluating Human Preferences for TexttoImage Generation
Imagine That! AbstracttoIntricate TexttoImage Synthesis with Scene Graph Hallucination Diffusion
Imbalanced Mixed Linear Regression
Imitation Learning from Vague Feedback
Implicit Bias of Gradient Descent for Twolayer ReLU and Leaky ReLU Networks on Nearlyorthogonal Data
Implicit Bias of Stochastic Gradient Descent for Rank1 Linear Neural Network
Implicit Contrastive Representation Learning with Guided Stopgradient
Implicit Convolutional Kernels for Steerable CNNs
Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis
Implicit Manifold Gaussian Process Regression
Implicit Regularization in OverParameterized Support Vector Machine
Implicit Transfer Operator Learning Multiple TimeResolution Models for Molecular Dynamics
Implicit variance regularization in noncontrastive SSL
Importanceaware Coteaching for Offline Modelbased Optimization
Importance Weighted ActorCritic for Optimal Conservative Offline Reinforcement Learning
IMPRESS Evaluating the Resilience of Imperceptible Perturbations Against Unauthorized Data Usage in DiffusionBased Generative AI
ImPromptu InContext Composition from Image Prompts
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning
Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition
Improved BestofBothWorlds Guarantees for MultiArmed Bandits FTRL with General Regularizers and Multiple Optimal Arms
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMMbased Gradient Updates
Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization
Improving Adversarial Robustness via Information Bottleneck Distillation
Improving Adversarial Transferability via Intermediatelevel Perturbation Decay
Improving CLIP Training with Language Rewrites
Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings
Improving dayahead Solar Irradiance Time Series Forecasting by Leveraging SpatioTemporal Context
Improving DiffusionBased Image Synthesis with Context Prediction
Improving FewShot Generalization by Exploring and Exploiting Auxiliary Data
Improving Graph Matching with Positional Reconstruction EncoderDecoder Network
Improving Language Plasticity via Pretraining with Active Forgetting
Improving neural network representations using human similarity judgments
Improving Robustness with Adaptive Weight Decay
Improving Selfsupervised Molecular Representation Learning using Persistent Homology
Improving the Knowledge Gradient Algorithm
Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners
Incentives in Federated Learning Equilibria, Dynamics, and Mechanisms for Welfare Maximization
Incentives in Private Collaborative Machine Learning
Incentivized Communication for Federated Bandits
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization
Incomplete MultimodalityDiffused Emotion Recognition
Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training
Individualized Dosing Dynamics via Neural Eigen Decomposition
Inferring Hybrid Neural Fluid Fields from Videos
InfoCD A Contrastive Chamfer Distance Loss for Point Cloud Completion
InfoPrompt InformationTheoretic Soft Prompt Tuning for Natural Language Understanding
Informationguided Planning An Online Approach for Partially Observable Problems
Information Design in MultiAgent Reinforcement Learning
Information Geometry of the Retinal Representation Manifol
Information Maximizing Curriculum A CurriculumBased Approach for Learning Versatile Skills
Information Theoretic Lower Bounds for Information Theoretic Upper Bounds
InitializationDependent Sample Complexity of Linear Predictors and Neural Networks
Initialization Matters PrivacyUtility Analysis of Overparameterized Neural Networks
Injecting Multimodal Information into Rigid Protein Docking via Bilevel Optimization
InnerOuter Aware Reconstruction Model for Monocular 3D Scene Reconstruction
Inner Productbased Neural Network Similarity
InsActor Instructiondriven Physicsbased Characters
Inserting Anybody in Diffusion Models via Celeb Basis
InstanT Semisupervised Learning with Instancedependent Thresholds
InstructBLIP Towards Generalpurpose VisionLanguage Models with Instruction Tuning
Instructing GoalConditioned Reinforcement Learning Agents with Temporal Logic Objectives
Integrationfree Training for Spatiotemporal Multimodal Covariate Deep Kernel Point Processes
Intensity Profile Projection A Framework for ContinuousTime Representation Learning for Dynamic Networks
Interaction Measures, Partition Lattices and Kernel Tests for HighOrder Interactions
Interactive Multifidelity Learning for Costeffective Adaptation of Language Model with Sparse Human Supervision
Interpretability at Scale Identifying Causal Mechanisms in Alpaca
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction
Interpretable Graph Networks Formulate Universal Algebra Conjectures
Interpretable Prototypebased Graph Information Bottleneck
Interpretable Reward Redistribution in Reinforcement Learning A Causal Approach
Intervention Generalization A View from Factor Graph Models
IntraModal Proxy Learning for ZeroShot Visual Categorization with CLIP
Intriguing Properties of Quantization at Scale
Intrinsic Dimension Estimation for Robust Detection of AIGenerated Texts
Invariant Anomaly Detection under Distribution Shifts A Causal Perspective
Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation
Inverse Preference Learning Preferencebased RL without a Reward Function
Inverse Reinforcement Learning with the Average Reward Criterion
Investigating how ReLUnetworks encode symmetries
In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer
IPMix LabelPreserving Data Augmentation Method for Training Robust Classifiers
iSCAN Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models
Isometric Quotient Variational AutoEncoders for StructurePreserving Representation Learning
ISP MultiLayered Garment Draping with Implicit Sewing Patterns
Is Distance Matrix Enough for Geometric Deep Learning
Is Heterogeneity Notorious Taming Heterogeneity to Handle TestTime Shift in Federated Learning
Is RLHF More Difficult than Standard RL A Theoretical Perspective
Is Your Code Generated by ChatGPT Really Correct Rigorous Evaluation of Large Language Models for Code Generation
Iteratively Learn Diverse Strategies with State Distance Information
Iterative Reachability Estimation for Safe Reinforcement Learning
Jaccard Metric Losses Optimizing the Jaccard Index with Soft Labels
Jigsaw Learning to Assemble Multiple Fractured Objects
Joint Attribute and Model Generalization Learning for PrivacyPreserving Action Recognition
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
Joint DataTask Generation for Auxiliary Learning
Joint Feature and Differentiable k NN Graph Learning using Dirichlet Energy
Joint Learning of Label and Environment Causal Independence for Graph OutofDistribution Generalization
Joint processing of linguistic properties in brains and language models
Joint Prompt Optimization of Stacked LLMs using Variational Inference
Joint Training of Deep Ensembles Fails Due to Learner Collusion
KAKURENBO Adaptively Hiding Samples in Deep Neural Network Training
KDZero Evolving Knowledge Distiller for Any TeacherStudent Pairs
Keep Various Trajectories Promoting Exploration of Ensemble Policies in Continuous Control
KernelBased Tests for LikelihoodFree Hypothesis Testing
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
Kernel Stein Discrepancy thinning a theoretical perspective of pathologies and a practical fix with regularization
KeypointAugmented SelfSupervised Learning for Medical Image Segmentation with Limited Annotation
Kissing to Find a Match Efficient LowRank Permutation Representation
kMeans Clustering with DistanceBased Privacy
kMedian Clustering via Metric Embedding Towards Better Initialization with Differential Privacy
KNearestNeighbor Local Sampling Based Conditional Independence Testing
KnowledgeAugmented Reasoning Distillation for Small Language Models in KnowledgeIntensive Tasks
Knowledge Diffusion for Distillation
Knowledge Distillation for High Dimensional Search Index
Knowledge Distillation Performs Partial Variance Reduction
Koopa Learning Nonstationary Time Series Dynamics with Koopman Predictors
Koopman Kernel Regression
KullbackLeibler Maillard Sampling for Multiarmed Bandits with Bounded Rewards
L2TDLN Learning to Teach with Dynamic Loss Network
Labelefficient Segmentation via Affinity Propagation
Labeling Neural Representations with Inverse Recognition
LabelOnly Model Inversion Attacks via Knowledge Transfer
LabelRetrievalAugmented Diffusion Models for Learning from Noisy Labels
Label Correction of Crowdsourced Noisy Annotations with an InstanceDependent Noise Transition Model
Label Poisoning is All You Nee
Label Robust and Differentially Private Linear Regression Computational and Statistical Efficiency
LaFTer LabelFree Tuning of Zeroshot Classifier using Language and Unlabeled Image Collections
LambdaBeam Neural Program Search with HigherOrder Functions and Lambdas
LANCE Stresstesting Visual Models by Generating Languageguided Counterfactual Images
Landscape Surrogate Learning Decision Losses for Mathematical Optimization Under Partial Information
Langevin QuasiMonte Carlo
Languagebased Action Concept Spaces Improve Video SelfSupervised Learning
Languagedriven Scene Synthesis using Multiconditional Diffusion Model
Language Is Not All You Need Aligning Perception with Language Models
Language Models are Weak Learners
Language Models Can Improve Event Prediction by FewShot Abductive Reasoning
Language Models can Solve Computer Tasks
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Language_Models_Don't_Always_Say_What_They_Think_Unfaithful_Explanations_in_ChainofThought_Prompting.pdf>Language Models Don't Always Say What They Think Unfaithful Explanations in ChainofThought Prompting
Language Models Meet World Models Embodied Experiences Enhance Language Models
Language Model Alignment with Elastic Reset
Language Model Tokenizers Introduce Unfairness Between Languages
Language Quantized AutoEncoders Towards Unsupervised TextImage Alignment
Language Semantic Graph Guided DataEfficient Learning
Laplacian Canonization A Minimalist Approach to Sign and Basis Invariant Spectral Embedding
LargeScale Distributed Learning via Private OnDevice LSH
Large Language Models Are Latent Variable Models Explaining and Finding Good Demonstrations for InContext Learning
Large Language Models Are SemiParametric Reinforcement Learning Agents
Large Language Models are Visual Reasoning Coordinators
Large Language Models Are ZeroShot Time Series Forecasters
Large Language Models as Commonsense Knowledge for LargeScale Task Planning
Large Language Models can Implement Policy Iteration
Large Language Models for Automated Data Science Introducing CAAFE for ContextAware Automated Feature Engineering
Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language
Large Language Models of Code Fail at Completing Code with Potential Bugs
Large language models transition from integrating across positionyoked, exponential windows to structureyoked, powerlaw windows
LART Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer
LastIterate Convergent Policy Gradient PrimalDual Methods for Constrained MDPs
Latent Diffusion for Language Generation
Latent exploration for Reinforcement Learning
Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
Latent Graph Inference with Limited Supervision
Latent SDEs on Homogeneous Spaces
Latent Space Translation via Semantic Alignment
Laughing Hyena Distillery Extracting Compact Recurrences From Convolutions
LayerNeighbor Sampling Defusing Neighborhood Explosion in GNNs
LayoutPrompter Awaken the Design Ability of Large Language Models
LC2ST Local Diagnostics for Posterior Approximations in SimulationBased Inference
LD2 Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
LEACE Perfect linear concept erasure in closed form
LearningtoRank Meets Language Boosting LanguageDriven Ordering Alignment for Ordinal Classification
Learning Adaptive Tensorial Density Fields for Clean CryoET Reconstruction
Learning Adversarial Lowrank Markov Decision Processes with Unknown Transition and Fullinformation Feedback
Learning and Collusion in Multiunit Auctions
Learning and processing the ordinal information of temporal sequences in recurrent neural circuits
Learning a 1layer conditional generative model in total variation
Learning a Neuron by a Shallow ReLU Network Dynamics and Implicit Bias for Correlated Inputs
Learning better with Dales Law A Spectral Perspective
Learning Better with Less Effective Augmentation for SampleEfficient Visual Reinforcement Learning
Learning Causal Models under Independent Changes
Learning Curves for Deep Structured Gaussian Feature Models
Learning Curves for Noisy Heterogeneous FeatureSubsampled Ridge Ensembles
Learning Cuts via Enumeration Oracles
Learning DAGs from Data with Few Root Causes
Learning Dense Flow Field for Highlyaccurate Crossview Camera Localization
Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation
Learning Dictionary for Visual Attention
Learning DomainAware Detection Head with Prompt Tuning
Learning Dynamic Attributefactored World Models for Efficient Multiobject Reinforcement Learning
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
Learning Energybased Model via DualMCMC Teaching
Learning EnergyBased Prior Model with DiffusionAmortized MCMC
Learning EnvironmentAware Affordance for 3D Articulated Object Manipulation under Occlusions
Learning Exponential Families from Truncated Samples
Learning Finegrained ViewInvariant Representations from Unpaired EgoExo Videos via Temporal Alignment
Learning From Biased Soft Labels
Learning from Both Structural and Textual Knowledge for Inductive Knowledge Graph Completion
Learning from Rich Semantics and Coarse Locations for Longtailed Object Detection
Learning from Visual Observation via Offline Pretrained StatetoGo Transformer
Learning Interpretable Lowdimensional Representation via Physical Symmetry
Learning Invariant Molecular Representation in Latent Discrete Space
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization
Learning Invariant Representations with a Nonparametric NadarayaWatson Hea
Learning in the Presence of Lowdimensional Structure A Spiked Random Matrix Perspective
Learning LargeScale MTP 2 Gaussian Graphical Models via BridgeBlock Decomposition
Learning Largescale Neural Fields via Context Pruned MetaLearning
Learning Large Graph Property Prediction via Graph Segment Training
Learning Maskaware CLIP Representations for ZeroShot Segmentation
Learning Mixtures of Gaussians Using the DDPM Objective
Learning Modulated Transformation in GANs
Learning Motion Refinement for Unsupervised Face Animation
Learning Multiagent Behaviors from Distributed and Streaming Demonstrations
Learning Neural Implicit through Volume Rendering with Attentive Depth Fusion Priors
Learning nonMarkovian DecisionMaking from Stateonly Sequences
Learning Nonparametric Latent Causal Graphs with Unknown Interventions
Learning Provably Robust Estimators for Inverse Problems via Jittering
Learning Rate Free Bayesian Inference in Constrained Domains
Learning Regularized Monotone Graphon MeanField Games
Learning Reliable Logical Rules with SATNet
Learning Repeatable Speech Embeddings Using An Intraclass Correlation Regularizer
Learning Resampling Methods with Parameter Attribution for Image Superresolution
Learning Robust Statistics for Simulationbased Inference under Model Misspecification
Learning RuleInduced Subgraph Representations for Inductive Relation Prediction
Learning Sample Difficulty from Pretrained Models for Reliable Prediction
Learning Scorebased Grasping Primitive for Humanassisting Dexterous Grasping
Learning Shared Safety Constraints from Multitask Demonstrations
Learning SpaceTime Continuous Latent Neural PDEs from Partially Observed States
Learning the Efficient Frontier
Learning threshold neurons via edge of stability
Learning TimeInvariant Representations for Individual Neurons from Population Dynamics
Learning TopologyAgnostic EEG Representations with GeometryAware Modeling
Learning to Augment Distributions for Outofdistribution Detection
Learning to Compress Prompts with Gist Tokens
Learning to Configure Separators in BranchandCut
Learning To Dive In Branch And Boun
Learning to Group Auxiliary Datasets for Molecule
Learning to Influence Human Behavior with Offline Reinforcement Learning
Learning to Modulate pretrained Models in RL
Learning to Parameterize Visual Attributes for Openset Finegrained Retrieval
Learning to Reason and Memorize with SelfNotes
Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural kOpt
Learning to Tokenize for Generative Retrieval
Learning Trajectories are Generalization Indicators
Learning Unseen Modality Interaction
Learning via WassersteinBased High Probability Generalisation Bounds
Learning Visual Prior via Generative PreTraining
Learning with Explanation Constraints
Learning World Models with Identifiable Factorization
Learn to Categorize or Categorize to Learn SelfCoding for Generalized Category Discovery
Leave No Stone Unturned Mine Extra Knowledge for Imbalanced Facial Expression Recognition
Lending Interaction Wings to Recommender Systems with Conversational Agents
LEPARD Learning Explicit Part Discovery for 3D Articulated Shape Reconstruction
Leveraging EarlyStage Robustness in Diffusion Models for Efficient and HighQuality Image Synthesis
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression
Leveraging Pretrained Large Language Models to Construct and Utilize World Models for Modelbased Task Planning
Leveraging the twotimescale regime to demonstrate convergence of neural networks
Leveraging VisionCentric MultiModal Expertise for 3D Object Detection
LICO Explainable Models with LanguageImage COnsistency
Lie Point Symmetry and PhysicsInformed Networks
Lift Yourself Up Retrievalaugmented Text Generation with SelfMemory
LightSpeed Light and Fast Neural Light Fields on Mobile Devices
Lightweight Vision Transformer with Bidirectional Interaction
LikelihoodBased Diffusion Language Models
Likelihood Ratio Confidence Sets for Sequential Decision Making
LIMA Less Is More for Alignment
Limits, approximation and size transferability for GNNs on sparse graphs via graphops
Linear Time Algorithms for kmeans with MultiSwap Local Search
LinGCN Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference
LLMPruner On the Structural Pruning of Large Language Models
LLMScore Unveiling the Power of Large Language Models in TexttoImage Synthesis Evaluation
LMC Large Model Collaboration with Crossassessment for TrainingFree OpenSet Object Recognition
LocalityAware Generalizable Implicit Neural Representation
Localized Symbolic Knowledge Distillation for Visual Commonsense Models
Locally Invariant Explanations Towards Stable and Unidirectional Explanations through Local Invariant Learning
Local Convergence of Gradient Methods for MinMax Games Partial Curvature Generically Suffices
Lockdown Backdoor Defense for Federated Learning with Isolated Subspace Training
LoCoOp FewShot OutofDistribution Detection via Prompt Learning
LogarithmicRegret Quantum Learning Algorithms for ZeroSum Games
Logarithmic Bayes Regret Bounds
LogSpecT Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees
LongTerm Fairness with Unknown Dynamics
Long Sequence Hopfield Memory
Lookaround Optimizer k steps around, 1 step average
Lookup Table meets Local Laplacian Filter Pyramid Reconstruction Network for Tone Mapping
Look Beneath the Surface Exploiting Fundamental Symmetry for SampleEfficient Offline RL
Look Ma, No Hands! AgentEnvironment Factorization of Egocentric Videos
Lossy Image Compression with Conditional Diffusion Models
Loss Decoupling for TaskAgnostic Continual Learning
Loss Dynamics of Temporal Difference Reinforcement Learning
Lovasz Principle for Unsupervised Graph Representation Learning
Lower Bounds on Adaptive Sensing for Matrix Recovery
Low Tensor Rank Learning of Neural Dynamics
LuminAIRe IlluminationAware Conditional Image Repainting for LightingRealistic Generation
LVMMed Learning LargeScale SelfSupervised Vision Models for Medical Imaging via Secondorder Graph Matching
L 2Uniform Stability of Randomized Learning Algorithms Sharper Generalization Bounds and Confidence Boosting
Machine learning detects terminal singularities
Macro Placement by WireMaskGuided BlackBox Optimization
MADG Marginbased Adversarial Learning for Domain Generalization
MAGGNN Reinforcement Learning Boosted Graph Neural Network
Make Pretrained Model Reversible From Parameter to Memory Efficient FineTuning
Make the U in UDA Matter Invariant Consistency Learning for Unsupervised Domain Adaptation
Making Scalable Meta Learning Practical
Managing Temporal Resolution in Continuous Value Estimation A Fundamental Tradeo
Manybody Approximation for Nonnegative Tensors
Marginal Density Ratio for OffPolicy Evaluation in Contextual Bandits
Marich A Queryefficient Distributionally Equivalent Model Extraction Attack
MarioGPT OpenEnded Text2Level Generation through Large Language Models
Markovian Sliced Wasserstein Distances Beyond Independent Projections
Masked Image Residual Learning for Scaling Deeper Vision Transformers
Masked Twochannel Decoupling Framework for Incomplete Multiview Weak Multilabel Learning
Mask Propagation for Efficient Video Semantic Segmentation
MassProducing Failures of Multimodal Systems with Language Models
MathNAS If Blocks Have a Role in Mathematical Architecture Design
Matrix Compression via Randomized Low Rank and Low Precision Factorization
MAViL Masked AudioVideo Learners
Maximum Average Randomly Sampled A Scale Free and Nonparametric Algorithm for Stochastic Bandits
Maximum Independent Set SelfTraining through Dynamic Programming
Maximum State Entropy Exploration using Predecessor and Successor Representations
MaxSliced Mutual Information
May the Force be with You Unified ForceCentric PreTraining for 3D Molecular Conformations
MCUFormer Deploying Vision Tranformers on Microcontrollers with Limited Memory
Mechanic A Learning Rate Tuner
MedUniC Unifying CrossLingual Medical VisionLanguage PreTraining by Diminishing Bias
Meek Separators and Their Applications in Targeted Causal Discovery
Meet in the Middle A New Pretraining Paradigm
MEGABYTE Predicting Millionbyte Sequences with Multiscale Transformers
MeGraph Capturing LongRange Interactions by Alternating Local and Hierarchical Aggregation on MultiScaled Graph Hierarchy
MemoryConstrained Algorithms for Convex Optimization
MemoryEfficient FineTuning of Compressed Large Language Models via sub4bit Integer Quantization
MEMTO Memoryguided Transformer for Multivariate Time Series Anomaly Detection
MetaAdaM An MetaLearned Adaptive Optimizer with Momentum for FewShot Learning
MetaAdapter An Online Fewshot Learner for VisionLanguage Model
Metaincontext learning in large language models
MetaLearning Adversarial Bandit Algorithms
Metalearning families of plasticity rules in recurrent spiking networks using simulationbased inference
MetaLearning with Neural Bandit Scheduler
Metis Understanding and Enhancing InNetwork Regular Expressions
Metropolis Sampling for Constrained Diffusion Models
MGViT A MultiGranularity Method for Compact and Efficient Vision Transformers
Michelangelo Conditional 3D Shape Generation based on ShapeImageText Aligned Latent Representation
MIM4DD Mutual Information Maximization for Dataset Distillation
MIMEx Intrinsic Rewards from Masked Input Modeling
MIMONets MultipleInputMultipleOutput Neural Networks Exploiting Computation in Superposition
Mind the spikes Benign overfitting of kernels and neural networks in fixed dimension
MinimaxOptimal Location Estimation
Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees
Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models
Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy
Minimum Description Length and Generalization Guarantees for Representation Learning
Minimum norm interpolation by perceptra Explicit regularization and implicit bias
MipGrid Antialiased Grid Representations for Neural Radiance Fields
Mirror Diffusion Models for Constrained and Watermarked Generation
Mitigating Oversmoothing in Transformers via Regularized Nonlocal Functionals
Mitigating Source Bias for Fairer Weak Supervision
Mitigating TestTime Bias for Fair Image Retrieval
Mitigating the Effect of Incidental Correlations on Partbased Learning
MixedInitiative Multiagent Apprenticeship Learning for Human Training of Robot Teams
Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation
MixFormerV2 Efficient Fully Transformer Tracking
MixofShow Decentralized LowRank Adaptation for MultiConcept Customization of Diffusion Models
Mixture Weight Estimation and Model Prediction in Multisource Multitarget Domain Adaptation
MKOR MomentumEnabled KroneckerFactorBased Optimizer Using Rank1 Updates
MMGP a Mesh Morphing Gaussian Processbased machine learning method for regression of physical problems under nonparametrized geometrical variability
Mnemosyne Learning to Train Transformers with Transformers
Mobilizing Personalized Federated Learning in InfrastructureLess and Heterogeneous Environments via Random Walk Stochastic ADMM
MoCa Measuring HumanLanguage Model Alignment on Causal and Moral Judgment Tasks
ModalityAgnostic SelfSupervised Learning with MetaLearned Masked AutoEncoder
ModalityIndependent Teachers Meet WeaklySupervised AudioVisual Event Parser
ModelBased Control with Sparse Neural Dynamics
ModelBased Reparameterization Policy Gradient Methods Theory and Practical Algorithms
Modelenhanced Vector Index
ModelFree Active Exploration in Reinforcement Learning
Modelfree Posterior Sampling via Learning Rate Randomization
ModelFree Reinforcement Learning with the DecisionEstimation Coefficient
Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message Passing
Modeling Human Visual Motion Processing with Trainable Motion Energy Sensing and a Selfattention Network
Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning
Model Shapley Equitable Model Valuation with Blackbox Access
Mode Connectivity in Auction Design
Modulated Neural ODEs
Modulewise Adaptive Distillation for Multimodality Foundation Models
Modulewise Training of Neural Networks via the Minimizing Movement Scheme
Molecule Joint AutoEncoding Trajectory Pretraining with 2D and 3D Diffusion
MomentDiff Generative Video Moment Retrieval from Random to Real
Momentum Provably Improves Error Feedback!
Moment Matching Denoising Gibbs Sampling
MonitorGuided Decoding of Code LMs with Static Analysis of Repository Context
MonoUNI A Unified Vehicle and Infrastructureside Monocular 3D Object Detection Network with Sufficient Depth Clues
Monte Carlo Tree Search with Boltzmann Exploration
Moral Responsibility for AI Systems
MosaicBERT A Bidirectional Encoder Optimized for Fast Pretraining
Most Neural Networks Are Almost Learnable
MotionGPT Human Motion as a Foreign Language
MoVie Visual ModelBased Policy Adaptation for View Generalization
MultiAgent First Order Constrained Optimization in Policy Space
MultiAgent Learning with Heterogeneous Linear Contextual Bandits
MultiAgent MetaReinforcement Learning Sharper Convergence Rates with Task Similarity
Multibody SE3 Equivariance for Unsupervised Rigid Segmentation and Motion Estimation
Multiclass Boosting Simple and Intuitive Weak Learning Criteria
MultiFidelity MultiArmed Bandits Revisite
MultiFusion Fusing PreTrained Models for MultiLingual, MultiModal Image Generation
MultiHead Adapter Routing for CrossTask Generalization
Multimodal Deep Learning Model Unveils Behavioral Dynamics of V1 Activity in Freely Moving Mice
MultiModal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations
Multimodal Queried Object Detection in the Wil
MultiMoDNMultimodal, MultiTask, Interpretable Modular Networks
Multinomial Logistic Regression Asymptotic Normality on Null Covariates in HighDimensions
MultiObjective Intrinsic Reward Learning for Conversational Recommender Systems
MultiPlayer ZeroSum Markov Games with Networked Separable Interactions
MultiplicationFree Transformer Training via Piecewise Affine Operations
Multiply Robust Federated Estimation of Targeted Average Treatment Effects
MultiPrompt Alignment for MultiSource Unsupervised Domain Adaptation
Multiresolution Spectral Coherence for Graph Generation with Scorebased Diffusion
Multiscale Diffusion Denoised Smoothing
MultiStep Generalized Policy Improvement by Leveraging Approximate Models
MultiSwap kMeans++
Multitask Graph Neural Architecture Search with Taskaware Collaboration and Curriculum
Multitask Learning with No Regret from Improved Confidence Bounds to Active Learning
Multitask learning with summary statistics
Multitask Representation Learning for Pure Exploration in Bilinear Bandits
MuSeGNN Learning Unified Gene Representation From Multimodal Biological Graph Data
MutualInformation Regularized MultiAgent Policy Iteration
Mutual Information Regularized Offline Reinforcement Learning
NAP Neural 3D Articulated Object Prior
NARFormer V2 Rethinking Transformer for Universal Neural Network Representation Learning
Nash Regret Guarantees for Linear Bandits
NASX Neural Adaptive Smoothing via Twisting
Natural ActorCritic for Robust Reinforcement Learning with Function Approximation
Natural Language Instructionfollowing with Taskrelated Language Development and Translation
Navigating Data Heterogeneity in Federated Learning A SemiSupervised Approach for Object Detection
Navigating the Pitfalls of Active Learning Evaluation A Systematic Framework for Meaningful Performance Assessment
NCDL A Framework for Deep Learning on nonCartesian Lattices
Nearest Neighbour with Bandit Feedback
NearLinear Time Algorithm for the Chamfer Distance
Nearly Optimal Bounds for Cyclic Forgetting
Nearly Optimal VCDimension and PseudoDimension Bounds for Deep Neural Network Derivatives
NearOptimal Algorithms for Gaussians with Huber Contamination Mean Estimation and Linear Regression
NearOptimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
NearOptimal kClustering in the Sliding Window Model
Near Optimal Reconstruction of Spherical Harmonic Expansions
Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming
NEOKD KnowledgeDistillationBased Adversarial Training for Robust MultiExit Neural Networks
NeRFIBVS Visual Servo Based on NeRF for Visual Localization and Navigation
NeRF Revisited Fixing Quadrature Instability in Volume Rendering
NetHack is Hard to Hack
Networks are Slacking Off Understanding Generalization Problem in Image Deraining
NeuralGF Unsupervised Point Normal Estimation by Learning Neural Gradient Function
NeuralLogic HumanObject Interaction Detection
Neural Algorithmic Reasoning Without Intermediate Supervision
Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions
Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb
Neural Combinatorial Optimization with Heavy Decoder Toward Large Scale Generalization
Neural Data Transformer 2 Multicontext Pretraining for Neural Spiking Activity
Neural Fields with Hard Constraints of Arbitrary Differential Order
Neural Frailty Machine Beyond proportional hazard assumption in neural survival regressions
Neural Functional Transformers
Neural Graph Generation from Graph Statistics
Neural Harmonics Bridging Spectral Embedding and Matrix Completion in SelfSupervised Learning
Neural Ideal Large Eddy Simulation Modeling Turbulence with Neural Stochastic Differential Equations
Neural Image Compression Generalization, Robustness, and Spectral Biases
Neural Lad A Neural Latent Dynamics Framework for Times Series Modeling
Neural Latent Geometry Search Product Manifold Inference via GromovHausdorffInformed Bayesian Optimization
Neural Lighting Simulation for Urban Scenes
Neural Lyapunov Control for DiscreteTime Systems
Neural Modulation for Flash Memory An Unsupervised Learning Framework for Improved Reliability
Neural MultiObjective Combinatorial Optimization with Diversity Enhancement
Neural Oscillators are Universal
Neural Polarizer A Lightweight and Effective Backdoor Defense via Purifying Poisoned Features
Neural Priming for SampleEfficient Adaptation
Neural Processes with Stability
Neural Relation Graph A Unified Framework for Identifying Label Noise and Outlier Data
Neural Sampling in Hierarchical Exponentialfamily Energybased Models
Neural Sculpting Uncovering hierarchically modular task structure in neural networks through pruning and network analysis
Neural Tangent Kernel Collapse
NeuroGF A Neural Representation for Fast Geodesic Distance and Path Queries
Neurosymbolic Learning Yielding Logical Constraints
New Bounds for Hyperparameter Tuning of Regression Problems Across Instances
New ComplexityTheoretic Frontiers of Tractability for Neural Network Training
NICE NoIsemodulated Consistency rEgularization for DataEfficient GANs
Noether Embedding Efficient Learning of Temporal Regularities
NoiseAdaptive Thompson Sampling for Linear Contextual Bandits
Nominality Score Conditioned Time Series Anomaly Detection by PointSequential Reconstruction
Nonadversarial training of Neural SDEs with signature kernel scores
Nonautoregressive Machine Translation with Probabilistic Contextfree Grammar
NonConvex Bilevel Optimization with TimeVarying Objective Functions
Nonparametric Boundary Geometry in Physics Informed Deep Learning
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Nonparametric Teaching for Multiple Learners
NonRigid Shape Registration via Deep Functional Maps Prior
NonSmooth WeaklyConvex Finitesum Coupled Compositional Optimization
NonStationary Bandits with AutoRegressive Temporal Dependency
Nonstationary Experimental Design under Linear Trends
Noregret Algorithms for Fair Resource Allocation
NoRegret Learning in Dynamic Competition with Reference Effects Under Logit Deman
NoRegret Learning with Unbounded Losses The Case of Logarithmic Pooling
NoRegret Online Prediction with Strategic Experts
NoRegret Online Reinforcement Learning with Adversarial Losses and Transitions
NormalizationEquivariant Neural Networks with Application to Image Denoising
Normalization Layers Are All That SharpnessAware Minimization Needs
Normbased Generalization Bounds for Sparse Neural Networks
Normguided latent space exploration for texttoimage generation
Not All NeuroSymbolic Concepts Are Created Equal Analysis and Mitigation of Reasoning Shortcuts
Not All OutofDistribution Data Are Harmful to OpenSet Active Learning
No Representation Rules Them All in Category Discovery
No Train No Gain Revisiting Efficient Training Algorithms For Transformerbased Language Models
NPCL Neural Processes for UncertaintyAware Continual Learning
NUMCC Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF
NuTrea Neural Tree Search for Contextguided Multihop KGQA
NVFi Neural Velocity Fields for 3D Physics Learning from Dynamic Videos
ObjectCentric Learning for RealWorld Videos by Predicting Temporal Feature Similarities
Objectcentric Learning with Cyclic Walks between Parts and Whole
OBJECT 3DIT Languageguided 3Daware Image Editing
ODEbased Recurrent Modelfree Reinforcement Learning for POMDPs
Offline Imitation Learning with Variational Counterfactual Reasoning
Offline Minimax SoftQlearning Under Realizability and Partial Coverage
Offline MultiAgent Reinforcement Learning with Implicit GlobaltoLocal Value Regularization
Offline Reinforcement Learning for MixtureofExpert Dialogue Management
Offline Reinforcement Learning with Differential Privacy
Offline RL with Discrete Proxy Representations for Generalizability in POMDPs
OffPolicy Evaluation for Human Feedback
One2345 Any Single Image to 3D Mesh in 45 Seconds without PerShape Optimization
OneforAll Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation
OneLineofCode Data Mollification Improves Optimization of Likelihoodbased Generative Models
OneNet Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling
OnePass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning
OneStep Diffusion Distillation via Deep Equilibrium Models
One Less Reason for Filter Pruning Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning
One Risk to Rule Them All A RiskSensitive Perspective on ModelBased Offline Reinforcement Learning
Online Adaptive Policy Selection in TimeVarying Systems NoRegret via Contractive Perturbations
Online Ad Allocation with Predictions
Online Ad Procurement in Nonstationary Autobidding Worlds
Online Clustering of Bandits with Misspecified User Models
Online Convex Optimization with Unbounded Memory
Online Corrupted User Detection and Regret Minimization
Online Inventory Problems Beyond the i.i.d. Setting with Online Convex Optimization
Online learning of longrange dependencies
Online Learning under Adversarial Nonlinear Constraints
Online Map Vectorization for Autonomous Driving A Rasterization Perspective
Online Nonstochastic ModelFree Reinforcement Learning
Online PCA in Converging Selfconsistent Field Equations
Online Performative Gradient Descent for Learning Nash Equilibria in DecisionDependent Games
Online POMDP Planning with Anytime Deterministic Guarantees
Online Pricing for MultiUser MultiItem Markets
Online robust nonstationary estimation
OntheFly Adapting Code Summarization on Trainable CostEffective Language Models
On Calibrating Diffusion Probabilistic Models
On Certified Generalization in Structured Prediction
On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data
On Computing Pairwise Statistics with Local Differential Privacy
On Convergence of Polynomial Approximations to the Gaussian Mixture Entropy
On Differentially Private Sampling from Gaussian and Product Distributions
On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes
On Evaluating Adversarial Robustness of Large VisionLanguage Models
On Generalization Bounds for Projective Clustering
On Imitation in Meanfield Games
On kernelbased statistical learning theory in the mean field limit
On Learning Latent Models with MultiInstance Weak Supervision
On Masked Pretraining and the Marginal Likelihoo
On Measuring Fairness in Generative Models
On permutation symmetries in Bayesian neural network posteriors a variational perspective
On Private and Robust Bandits
On Proper Learnability between Average and Worstcase Robustness
On Robust Streaming for Learning with Experts Algorithms and Lower Bounds
On SampleEfficient Offline Reinforcement Learning Data Diversity, Posterior Sampling and Beyon
On Separate Normalization in Selfsupervised Transformers
On SingleIndex Models beyond Gaussian Data
On skip connections and normalisation layers in deep optimisation
On Slicing Optimality for Mutual Information
On Sparse Modern Hopfield Model
On studentteacher deviations in distillation does it pay to disobey
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
On the Adversarial Robustness of Outofdistribution Generalization Models
On the Asymptotic Learning Curves of Kernel Ridge Regression under Powerlaw Decay
On the choice of Perception Loss Function for Learned Video Compression
On the Complexity of Differentially Private BestArm Identification with Fixed Confidence
On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis
On the Constrained TimeSeries Generation Problem
On the Convergence and Sample Complexity Analysis of Deep QNetworks with epsilonGreedy Exploration
On the Convergence of BlackBox Variational Inference
On the Convergence of CART under Sufficient Impurity Decrease Condition
On the Convergence of Encoderonly Shallow Transformers
On the Convergence of NoRegret Learning Dynamics in TimeVarying Games
On the Convergence to a Global Solution of ShufflingType Gradient Algorithms
On the explainable properties of 1Lipschitz Neural Networks An Optimal Transport Perspective
On the Exploitability of Instruction Tuning
On the Exploration of Local Significant Differences For TwoSample Test
On the Generalization Error of Stochastic Mirror Descent for QuadraticallyBounded Losses an Improved Analysis
On the Generalization Properties of Diffusion Models
On the Identifiability and Interpretability of Gaussian Process Models
On the Identifiability of Sparse ICA without Assuming NonGaussianity
On the impact of activation and normalization in obtaining isometric embeddings at initialization
On the Implicit Bias of Linear Equivariant Steerable Networks
On the Importance of Exploration for Generalization in Reinforcement Learning
On the Importance of Feature Separability in Predicting OutOfDistribution Error
On the Interplay between Social Welfare and Tractability of Equilibria
On the Lastiterate Convergence in Timevarying Zerosum Games Extra Gradient Succeeds where Optimism Fails
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them A GradientNorm Perspective
On the Overlooked Structure of Stochastic Gradients
On the Pareto Front of Multilingual Neural Machine Translation
On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection
On the Power of SVD in the Stochastic Block Model
On the Properties of KullbackLeibler Divergence Between Multivariate Gaussian Distributions
On the Relationship Between Relevance and Conflict in Online Social Link Recommendations
On the Robustness of Mechanism Design under Total Variation Distance
On the Robustness of RemovalBased Feature Attributions
On the Role of Entanglement and Statistics in Learning
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks Exponential Gaps for Long Sequences
On the Size and Approximation Error of Distilled Datasets
On the spectral bias of twolayer linear networks
On the StabilityPlasticity Dilemma in Continual MetaLearning Theory and Algorithm
On the Statistical Consistency of RiskSensitive Bayesian DecisionMaking
On the Sublinear Regret of GPUCB
On the Tradeoff of IntraInterclass Diversity for Supervised Pretraining
On Transfer of Adversarial Robustness from Pretraining to Downstream Tasks
Opening the Vocabulary of Egocentric Actions
OpenMask3D OpenVocabulary 3D Instance Segmentation
OpenShape Scaling Up 3D Shape Representation Towards OpenWorld Understanding
OpenVocabulary Semantic Segmentation via Attribute DecompositionAggregation
Open Compound Domain Adaptation with Object Style Compensation for Semantic Segmentation
Open Visual Knowledge Extraction via RelationOriented Multimodality Model Prompting
OperationLevel Early Stopping for Robustifying Differentiable NAS
Operator Learning with Neural Fields Tackling PDEs on General Geometries
Optimality in Mean Estimation Beyond WorstCase, Beyond SubGaussian, and Beyond 1+alpha Moments
Optimality of MessagePassing Architectures for Sparse Graphs
Optimal Algorithms for the Inhomogeneous Spiked Wigner Model
Optimal and Fair Encouragement Policy Evaluation and Learning
Optimal approximation using complexvalued neural networks
Optimal Blockwise Asymmetric Graph Construction for Graphbased Semisupervised Learning
Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes
Optimal crosslearning for contextual bandits with unknown context distributions
Optimal Excess Risk Bounds for Empirical Risk Minimization on pNorm Linear Regression
Optimal ExtragradientBased Algorithms for Stochastic Variational Inequalities with Separable Structure
Optimal Parameter and Neuron Pruning for OutofDistribution Detection
Optimal Preconditioning and Fisher Adaptive Langevin Sampling
Optimal privacy guarantees for a relaxed threat model Addressing suboptimal adversaries in differentially private machine learning
Optimal Rates for Bandit Nonstochastic Control
Optimal Regret Is Achievable with Bounded Approximate Inference Error An Enhanced Bayesian Upper Confidence Bound Framework
Optimal testing using combined test statistics across independent studies
Optimal Time Complexities of Parallel Stochastic Optimization Methods Under a Fixed Computation Model
Optimal TransportGuided Conditional ScoreBased Diffusion Model
Optimal Transport for Treatment Effect Estimation
Optimal Transport Model Distributional Robustness
Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making
Optimal Treatment Regimes for Proximal Causal Learning
Optimal Unbiased Randomizers for Regression with Label Differential Privacy
Optimistic Active Exploration of Dynamical Systems
Optimistic Exploration in Reinforcement Learning Using Symbolic Model Estimates
Optimistic MetaGradients
Optimistic Rates for MultiTask Representation Learning
Optimization and Bayes A Tradeoff for Overparameterized Neural Networks
Optimization of Intergroup criteria for clustering with minimum size constraints
Optimization or Architecture How to Hack Kalman Filtering
Optimized Covariance Design for AB Test on Social Network under Interference
Optimize Planning Heuristics to Rank, not to Estimate CosttoGoal
Optimizing over trained GNNs via symmetry breaking
Oracle Complexity of SingleLoop Switching Subgradient Methods for NonSmooth Weakly Convex Functional Constrained Optimization
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning
Orthogonal Nonnegative Tensor Factorization based Multiview Clustering
OutlierRobust Wasserstein DRO
Outofdistribution Detection Learning with Unreliable Outofdistribution Sources
Overcoming Recency Bias of Normalization Statistics in Continual Learning Balance and Adaptation
PACBayesian SpectrallyNormalized Bounds for Adversarially Robust Generalization
PACBayes Generalization Certificates for Learned Inductive Conformal Prediction
PackQViT Faster Sub8bit Vision Transformers via Full and Packed Quantization on the Mobile
PaintSeg Painting Pixels for Trainingfree Segmentation
Pairwise Causality Guided Transformers for Event Sequences
PanoGen TextConditioned Panoramic Environment Generation for VisionandLanguage Navigation
PanoGRF Generalizable Spherical Radiance Fields for Widebaseline Panoramas
ParaFuzz An InterpretabilityDriven Technique for Detecting Poisoned Samples in NLP
Parallelmentoring for Offline Modelbased Optimization
Parallel Spiking Neurons with High Efficiency and Ability to Learn Longterm Dependencies
Parameterefficient Tuning of Largescale Multimodal Foundation Model
Parameterizing Context Unleashing the Power of ParameterEfficient FineTuning and InContext Tuning for Continual Table Semantic Parsing
Parameterizing NonParametric MetaReinforcement Learning Tasks via Subtask Decomposition
Parameter and Computation Efficient Transfer Learning for VisionLanguage Pretrained Models
Paraphrasing evades detectors of AIgenerated text, but retrieval is an effective defense
Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage
Partial Matrix Completion
Partial MultiLabel Learning with Probabilistic Graphical Disambiguation
Particlebased Variational Inference with Generalized Wasserstein Gradient Flow
Parts of Speech Grounded Subspaces in VisionLanguage Models
Passive learning of active causal strategies in agents and language models
Patch Diffusion Faster and More DataEfficient Training of Diffusion Models
Patch n Pack NaViT, a Vision Transformer for any Aspect Ratio and Resolution
Path following algorithms for ell 2regularized Mestimation with approximation guarantee
Path Regularization A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
Payoffbased Learning with Matrix Multiplicative Weights in Quantum Games
PCFGAN generating sequential data via the characteristic function of measures on the path space
PDF Point Diffusion Implicit Function for Largescale Scene Neural Representation
PDP Parameterfree Differentiable Pruning is All You Nee
Penalising the biases in norm regularisation enforces sparsity
Pengi An Audio Language Model for Audio Tasks
Penguin ParallelPacked Homomorphic Encryption for Fast Graph Convolutional Network Inference
Percentile Criterion Optimization in Offline Reinforcement Learning
Perceptual adjustment queries and an inverted measurement paradigm for lowrank metric learning
Perceptual Kalman Filters Online State Estimation under a Perfect PerceptualQuality Constraint
PERFOGRAPH A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis
Performanceoptimized deep neural networks are evolving into worse models of inferotemporal visual cortex
Performance Bounds for PolicyBased Average Reward Reinforcement Learning Algorithms
Performance Scaling via Optimal Transport Enabling Data Selection from Partially Revealed Sources
Permutation Equivariant Neural Functionals
Personalized Dictionary Learning for Heterogeneous Datasets
Persuading Farsighted Receivers in MDPs the Power of Honesty
Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability
PETAL Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
PFlow A Fast and DataEfficient ZeroShot TTS through Speech Prompting
PGDiff Guiding Diffusion Models for Versatile Face Restoration via Partial Guidance
Phase diagram of early training dynamics in deep neural networks effect of the learning rate, depth, and width
PHOTOSWAP Personalized Subject Swapping in Images
PhysicsInformed Bayesian Optimization of Variational Quantum Circuits
PickaPic An Open Dataset of User Preferences for TexttoImage Generation
PICProp PhysicsInformed Confidence Propagation for Uncertainty Quantification
PIDInspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks
Pitfall of Optimism Distributional Reinforcement Learning by Randomizing Risk Criterion
PlanE Representation Learning over Planar Graphs
PLANNER Generating Diversified Paragraph via Latent Language Diffusion Model
PLASTIC Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning
PoET A generative model of protein families as sequencesofsequences
PointGPT Autoregressively Generative Pretraining from Point Clouds
Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior
Point Cloud Completion with Pretrained TexttoImage Diffusion Models
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data
Policy Gradient for Rectangular Robust Markov Decision Processes
Policy Optimization for Continuous Reinforcement Learning
Policy Optimization in a Noisy Neighborhood On Return Landscapes in Continuous Control
Policy Space Diversity for NonTransitive Games
PolyDiffuse Polygonal Shape Reconstruction via Guided Set Diffusion Models
Polyhedron Attention Module Learning Adaptiveorder Interactions
Polynomially OverParameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets
PolynomialTime LinearSwap Regret Minimization in ImperfectInformation Sequential Games
POMDP Planning for Object Search in Partially Unknown Environment
POP3D OpenVocabulary 3D Occupancy Prediction from Images
Posterior Sampling for Competitive RL Function Approximation and Partial Observation
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation
Posthoc privacy guarantees for collaborative inference with modified ProposeTestRelease
Postprocessing Private Synthetic Data for Improving Utility on Selected Measures
Post Hoc Explanations of Language Models Can Improve Language Models
PPi Pretraining Brain Signal Model for Patientindependent Seizure Detection
pPoisson surface reconstruction in curlfree flow from point clouds
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Practical Contextual Bandits with Feedback Graphs
Practical Differentially Private Hyperparameter Tuning with Subsampling
Practical Equivariances via Relational Conditional Neural Processes
PrecisionRecall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows
Preconditioning Matters Fast Global Convergence of Nonconvex Matrix Factorization via Scaled Gradient Descent
Predict, Refine, Synthesize SelfGuiding Diffusion Models for Probabilistic Time Series Forecasting
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Predicting_a_Protein's_Stability_under_a_Million_Mutations.pdf>Predicting a Protein's Stability under a Million Mutations
Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily
Predicting mutational effects on proteinprotein binding via a sidechain diffusion probabilistic model
Prediction and Control in Continual Reinforcement Learning
PredictthenCalibrate A New Perspective of Robust Contextual LP
PreDiff Precipitation Nowcasting with Latent Diffusion Models
PRED Pretraining via Semantic Rendering on LiDAR Point Clouds
Preferencegrounded Tokenlevel Guidance for Language Model Finetuning
Pretraining Contextualized World Models with Inthewild Videos for Reinforcement Learning
Pretraining task diversity and the emergence of nonBayesian incontext learning for regression
PrimalAttention Selfattention through Asymmetric Kernel SVD in Primal Representation
PrimDiffusion Volumetric Primitives Diffusion for 3D Human Generation
Principled Weight Initialisation for InputConvex Neural Networks
PriorBand Practical Hyperparameter Optimization in the Age of Deep Learning
Prioritizing Samples in Reinforcement Learning with Reducible Loss
PRIOR Personalized Prior for Reactivating the Information Overlooked in Federated Learning
Privacy Amplification via Compression Achieving the Optimal PrivacyAccuracyCommunication Tradeoff in Distributed Mean Estimation
Private Federated Frequency Estimation Adapting to the Hardness of the Instance
Probabilistic Exponential Integrators
Probabilistic Inference in Reinforcement Learning Done Right
Probabilistic Invariant Learning with Randomized Linear Classifiers
Probabilistic inverse optimal control for nonlinear partially observable systems disentangles perceptual uncertainty and behavioral costs
Probabilistic Weight Fixing Largescale training of neural network weight uncertainties for quantisation
PrObeD Proactive Object Detection Wrapper
Progressive Ensemble Distillation Building Ensembles for Efficient Inference
ProjectionFree Methods for Solving NonconvexConcave Saddle Point Problems
ProjectionFree Methods for Stochastic Simple Bilevel Optimization with Convex Lowerlevel Problem
ProjectionFree Online Convex Optimization via Efficient Newton Iterations
Projection Regret Reducing Background Bias for Novelty Detection via Diffusion Models
Promptaugmented Temporal Point Process for Streaming Event Sequence
PromptIR Prompting for AllinOne Image Restoration
PromptRestorer A Prompting Image Restoration Method with Degradation Perception
Prompt PreTraining with TwentyThousand Classes for OpenVocabulary Visual Recognition
Propagating Knowledge Updates to LMs Through Distillation
Proportional Response Contextual Bandits for Simple and Cumulative Regret Minimization
ProteinNPT Improving protein property prediction and design with nonparametric transformers
PROTES Probabilistic Optimization with Tensor Sampling
ProtoDiff Learning to Learn Prototypical Networks by TaskGuided Diffusion
Prototypebased Aleatoric Uncertainty Quantification for Crossmodal Retrieval
Prototypical Variational Autoencoder for 3D Fewshot Object Detection
Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs
Provable Adversarial Robustness for Group Equivariant Tasks Graphs, Point Clouds, Molecules, and More
Provable convergence guarantees for blackbox variational inference
Provable Guarantees for Generative Behavior Cloning Bridging LowLevel Stability and HighLevel Behavior
Provable Guarantees for Neural Networks via Gradient Feature Learning
Provably Efficient Algorithm for Nonstationary LowRank MDPs
Provably Efficient Offline GoalConditioned Reinforcement Learning with General Function Approximation and SinglePolicy Concentrability
Provably Efficient Offline Reinforcement Learning in Regular Decision Processes
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games
Provably More SampleEfficient Offline RL with Options
Provably Robust Temporal Difference Learning for HeavyTailed Rewards
Provably Safe Reinforcement Learning with Stepwise Violation Constraints
Pruning vs Quantization Which is Better
PseudoLikelihood Inference
PTQD Accurate PostTraining Quantization for Diffusion Models
Public Opinion Field Effect Fusion in Representation Learning for Trending Topics Diffusion
PUCA PatchUnshuffle and Channel Attention for Enhanced SelfSupervised Image Denoising
PUe Biased PositiveUnlabeled Learning Enhancement by Causal Inference
Punctuationlevel Attack Singleshot and Single Punctuation Can Fool Text Models
pvalue Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison
PyNeRF Pyramidal Neural Radiance Fields
QDM An Efficient Lowbit Quantized Diffusion Model
QuadAttacK A Quadratic Programming Approach to Learning Ordered TopK Adversarial Attacks
Quantification of Uncertainty with Adversarial Models
Quantifying & Modeling Multimodal Interactions An Information Decomposition Framework
Quantifying the Cost of Learning in Queueing Systems
Quantizable Transformers Removing Outliers by Helping Attention Heads Do Nothing
Quantum Bayesian Optimization
Quantum speedups for stochastic optimization
Querybased Temporal Fusion with Explicit Motion for 3D Object Detection
RADAR Robust AIText Detection via Adversarial Learning
RandomAccess Infinite Context Length for Transformers
Randomized and Deterministic Maximinshare Approximations for Fractionally Subadditive Valuations
RangePerception Taming LiDAR Range View for Efficient and Accurate 3D Object Detection
Rank1 Matrix Completion with Gradient Descent and Small Random Initialization
RankDETR for High Quality Object Detection
RanPAC Random Projections and Pretrained Models for Continual Learning
RAPHAEL TexttoImage Generation via Large Mixture of Diffusion Paths
RayDF Neural Raysurface Distance Fields with Multiview Consistency
Rdivergence for Estimating Modeloriented Distribution Discrepancy
RDumb A simple approach that questions our progress in continual testtime adaptation
Reading Relevant Feature from Global Representation Memory for Visual Object Tracking
Read and Reap the Rewards Learning to Play Atari with the Help of Instruction Manuals
RealTime Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding
RealWorld Image SuperResolution as MultiTask Learning
Recaptured Raw Screen Image and Video Demoiring via Channel and Spatial Modulations
Recasting Continual Learning as Sequence Modeling
RECESS Vaccine for Federated Learning Proactive Defense Against Model Poisoning Attacks
RECKONING Reasoning through Dynamic Knowledge Encoding
Recommender Systems with Generative Retrieval
Reconciling Competing Sampling Strategies of Network Embedding
ReContrast DomainSpecific Anomaly Detection via Contrastive Reconstruction
Recovering from Outofsample States via Inverse Dynamics in Offline Reinforcement Learning
Recovering Simultaneously Structured Data via NonConvex Iteratively Reweighted Least Squares
Recovering Unbalanced Communities in the Stochastic Block Model with Application to Clustering with a Faulty Oracle
Recurrent Hypernetworks are Surprisingly Strong in MetaRL
Recurrent Temporal Revision Graph Networks
Recursion in Recursion TwoLevel Nested Recursion for Length Generalization with Scalability
ReDS Offline RL With Heteroskedastic Datasets via Support Constraints
Reduced Policy Optimization for Continuous Control with Hard Constraints
Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor
Reducing ShapeRadiance Ambiguity in Radiance Fields with a ClosedForm Color Estimation Metho
Red Teaming Deep Neural Networks with Feature Synthesis Tools
ReferenceBased POMDPs
Refined Mechanism Design for Approximately Structured Priors via Active Regression
REFINE A FineGrained Medication Recommendation System Using Deep Learning and Personalized Drug Interaction Modeling
Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans
Reflexion language agents with verbal reinforcement learning
RegBN Batch Normalization of Multimodal Data with Regularization
Regression with Costbased Rejection
RegretOptimal ModelFree Reinforcement Learning for Discounted MDPs with Short BurnIn Time
Regret Minimization via Saddle Point Optimization
Regularity as Intrinsic Reward for Free Play
Regularizing Neural Networks with MetaLearning Generative Models
Rehearsal Learning for Avoiding Undesired Future
ReHLine Regularized Composite ReLUReHU Loss Minimization with Linear Computation and Linear Convergence
Reinforcement Learning for Finetuning TexttoImage Diffusion Models
Reinforcement Learning with Fast and Forgetful Memory
Reinforcement Learning with Simple Sequence Priors
Reining Generalization in Offline Reinforcement Learning via Representation Distinction
Relative Entropic Optimal Transport a Prioraware Matching Perspective to Unbalanced Classification
Reliable learning in challenging environments
Reliable OffPolicy Learning for Dosage Combinations
ReMaX Relaxing for Better Training on Efficient Panoptic Segmentation
Removing Hidden Confounding in Recommendation A Unified MultiTask Learning Approach
Repetition In Repetition Out Towards Understanding Neural Text Degeneration from the Data Perspective
Replicability in Reinforcement Learning
Replicable Clustering
Replicable Reinforcement Learning
Representational Strengths and Limitations of Transformers
Representation Equivalent Neural Operators a Framework for Aliasfree Operator Learning
Representation Learning via Consistent Assignment of Views over Random Partitions
Reproducibility in Multiple Instance Learning A Case For Algorithmic Unit Tests
Resetting the Optimizer in Deep RL An Empirical Study
Residual Alignment Uncovering the Mechanisms of Residual Networks
Residual QLearning Offline and Online Policy Customization without Value
Resilient Constrained Learning
Resilient Multiple Choice Learning A learned scoring scheme with application to audio scene analysis
ResMem Learn what you can and memorize the rest
Resolving the TugofWar A Separation of Communication and Learning in Federated Learning
ResoNet NoiseTrained PhysicsInformed MRI OffResonance Correction
Response Length Perception and Sequence Scheduling An LLMEmpowered LLM Inference Pipeline
Responsible AI RAI Games and Ensembles
Restart Sampling for Improving Generative Processes
ResTuning A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone
ReSync Riemannian Subgradientbased Robust Rotation Synchronization
Retaining Beneficial Information from Detrimental Data for Neural Network Repair
Rethinking Conditional Diffusion Sampling with Progressive Guidance
Rethinking GaussNewton for learning overparameterized models
Rethinking Incentives in Recommender Systems Are Monotone Rewards Always Beneficial
Rethinking SemiSupervised Imbalanced Node Classification from BiasVariance Decomposition
Rethinking SemiSupervised Medical Image Segmentation A VarianceReduction Perspective
Rethinking the Backward Propagation for Adversarial Transferability
Rethinking the Role of Token Retrieval in MultiVector Retrieval
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules
ReThink and ReDesign Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals
RetrievalAugmented Multiple Instance Learning
ReTR Modeling Rendering Via Transformer for Generalizable Neural Surface Reconstruction
RETVec Resilient and Efficient Text Vectorizer
Reusable Slotwise Mechanisms
Reusing Pretrained Models by Multilinear Operators for Efficient Training
RevColV2 Exploring Disentangled Representations in Masked Image Modeling
Reverse Engineering SelfSupervised Learning
Reversible and irreversible bracketbased dynamics for deep graph neural networks
Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness
Revisiting Adversarial Training for ImageNet Architectures, Training and Generalization across Threat Models
Revisiting Area Convexity Faster BoxSimplex Games and Spectrahedral Generalizations
Revisiting Implicit Differentiation for Learning Problems in Optimal Control
Revisiting Logisticsoftmax Likelihood in Bayesian MetaLearning for FewShot Classification
Revisiting Scalarization in MultiTask Learning A Theoretical Perspective
Revisiting the Minimalist Approach to Offline Reinforcement Learning
Revisiting Visual Model Robustness A Frequency LongTailed Distribution View
Revisit the Power of Vanilla Knowledge Distillation from Small Scale to Large Scale
Revisit WeaklySupervised AudioVisual Video Parsing from the Language Perspective
Rewardagnostic Finetuning Provable Statistical Benefits of Hybrid Reinforcement Learning
RewardDirected Conditional Diffusion Provable Distribution Estimation and Reward Improvement
Rewarded soups towards Paretooptimal alignment by interpolating weights finetuned on diverse rewards
Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery
Reward Imputation with Sketching for Contextual Batched Bandits
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks
Rewrite Caption Semantics Bridging Semantic Gaps for LanguageSupervised Semantic Segmentation
REx DataFree Residual Quantization Error Expansion
RGMIL Guide Your MultipleInstance Learning Model with Regressor
RHBrainFS Regional Heterogeneous Multimodal Brain Networks Fusion Strategy
Riemannian Laplace approximations for Bayesian neural networks
Riemannian Projectionfree Online Learning
Riemannian Residual Neural Networks
Riemannian SAM SharpnessAware Minimization on Riemannian Manifolds
Riemannian stochastic optimization methods avoid strict saddle points
Rigorous Runtime Analysis of MOEAD for Solving MultiObjective Minimum Weight Base Problems
RiskAverse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning
RiskQ Risksensitive MultiAgent Reinforcement Learning Value Factorization
RLbased Stateful Neural Adaptive Sampling and Denoising for RealTime Path Tracing
RoboCLIP One Demonstration is Enough to Learn Robot Policies
Robustifying Generalizable Implicit Shape Networks with a Tunable NonParametric Model
Robustness Guarantees for Adversarially Trained Neural Networks
Robust and Actively Secure Serverless Collaborative Learning
Robust Bayesian Satisficing
Robust Concept Erasure via Kernelized RateDistortion Maximization
Robust Contrastive LanguageImage Pretraining against Data Poisoning and Backdoor Attacks
Robust covariance estimation with missing values and cellwise contamination
Robust Data Pruning under Label Noise via Maximizing Relabeling Accuracy
Robust Data Valuation with Weighted Banzhaf Values
Robust Knowledge Transfer in Tiered Reinforcement Learning
Robust Learning for Smoothed Online Convex Optimization with Feedback Delay
Robust Learning with Progressive Data Expansion Against Spurious Correlation
Robust Lipschitz Bandits to Adversarial Corruptions
Robust lowrank training via approximate orthonormal constraints
Robust Matrix Sensing in the SemiRandom Model
Robust Mean Estimation Without Moments for Symmetric Distributions
Robust MultiAgent Reinforcement Learning via Adversarial Regularization Theoretical Foundation and Stable Algorithms
Robust SecondOrder Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
RRHF Rank Responses to Align Language Models with Human Feedback
RSDel Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Rubik's_Cube_HighOrder_Channel_Interactions_with_a_Hierarchical_Receptive_Field.pdf>Rubik's Cube HighOrder Channel Interactions with a Hierarchical Receptive Fiel
SafeDICE Offline Safe Imitation Learning with NonPreferred Demonstrations
Safe Exploration in Reinforcement Learning A Generalized Formulation and Algorithms
SALSA VERDE a machine learning attack on LWE with sparse small secrets
SAMoSSA Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise
SampleConditioned Hypothesis Stability Sharpens InformationTheoretic Generalization Bounds
SampleEfficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents
Sampleefficient Multiobjective Molecular Optimization with GFlowNets
Sample based Explanations via Generalized Representers
Sample Complexity Bounds for ScoreMatching Causal Discovery and Generative Modeling
Sample Complexity for Quadratic Bandits Hessian Dependent Bounds and Optimal Algorithms
Sample Complexity of GoalConditioned Hierarchical Reinforcement Learning
Sampling from Structured LogConcave Distributions via a SoftThreshold Dikin Walk
Sampling weights of deep neural networks
SANFlow SemanticAware Normalizing Flow for Anomaly Detection
SASolver Stochastic Adams Solver for Fast Sampling of Diffusion Models
SatLM SatisfiabilityAided Language Models Using Declarative Prompting
SaVeNet A Scalable Vector Network for Enhanced Molecular Representation Learning
Saving 100x Storage Prototype Replay for Reconstructing Training Sample Distribution in ClassIncremental Semantic Segmentation
Scalable Fair Influence Maximization
Scalable Membership Inference Attacks via Quantile Regression
Scalable PrimalDual ActorCritic Method for Safe MultiAgent RL with General Utilities
Scalable Transformer for PDE Surrogate Modeling
Scalarization for MultiTask and MultiDomain Learning at Scale
ScaleLong Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection
ScaleSpace Hypernetworks for Efficient Biomedical Image Analysis
Scaleteaching Robust Multiscale Training for Time Series Classification with Noisy Labels
Scaling Laws for Hyperparameter Optimization
Scaling laws for language encoding models in fMRI
Scaling MLPs A Tale of Inductive Bias
Scaling Riemannian Diffusion Models
Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster FrankWolfe Iterations
Scan and Snap Understanding Training Dynamics and Token Composition in 1layer Transformer
Scattering Vision Transformer Spectral Mixing Matters
Scenario Diffusion Controllable Driving Scenario Generation With Diffusion
SceneScape TextDriven Consistent Scene Generation
Scissorhands Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time
SCLIP Semisupervised VisionLanguage Learning using Few Specialist Captions
Scorebased Data Assimilation
Scorebased Source Separation with Applications to Digital Communication Signals
SE3 Diffusion Modelbased Point Cloud Registration for Robust 6D Object Pose Estimation
Searching for Optimal PerCoordinate Stepsizes with Multidimensional Backtracking
Secure OutofDistribution Task Generalization with EnergyBased Models
SEEDS Exponential SDE Solvers for Fast HighQuality Sampling from Diffusion Models
Seeing is not Believing Robust Reinforcement Learning against Spurious Correlation
SEENN Towards Temporal Spiking Early Exit Neural Networks
SEGA Instructing TexttoImage Models using Semantic Guidance
Segment Anything in 3D with NeRFs
Segment Anything in High Quality
Segment Everything Everywhere All at Once
SegRefiner Towards ModelAgnostic Segmentation Refinement with Discrete Diffusion Process
Selectively Sharing Experiences Improves MultiAgent Reinforcement Learning
Selective Sampling and Imitation Learning via Online Regression
Selectivity Drives Productivity Efficient Dataset Pruning for Enhanced Transfer Learning
SelfAdaptive Motion Tracking against Onbody Displacement of Flexible Sensors
SelfChained ImageLanguage Model for Video Localization and Question Answering
SelfConsistent Velocity Matching of Probability Flows
SelfCorrecting Bayesian Optimization through Bayesian Active Learning
SelfEvaluation Guided Beam Search for Reasoning
SelfPredictive Universal AI
SelfRefine Iterative Refinement with SelfFeedback
Selfsupervised Graph Neural Networks via LowRank Decomposition
SelfSupervised Learning of Representations for Space Generates MultiModular Grid Cells
SelfSupervised Learning with Lie Symmetries for Partial Differential Equations
SelfSupervised Motion Magnification by Backpropagating Through Optical Flow
Selfsupervised ObjectCentric Learning for Videos
SelfSupervised Reinforcement Learning that Transfers using Random Features
Selfsupervised video pretraining yields robust and more humanaligned visual representations
SelfSupervised Visual Acoustic Matching
SelfWeighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration
Semantic HELM A HumanReadable Memory for Reinforcement Learning
Semantic Image Synthesis with Unconditional Generator
Semantic segmentation of sparse irregular point clouds for leafwood discrimination
SemiImplicit Denoising Diffusion Models SIDDMs
SemiSupervised Contrastive Learning for Deep Regression with Ordinal Rankings from Spectral Seriation
Sensitivity in Translation Averaging
Sequential Memory with Temporal Predictive Coding
Sequential Predictive TwoSample and Independence Testing
Sequential Preference Ranking for Efficient Reinforcement Learning from Human Feedback
Sequential Subset Matching for Dataset Distillation
Setting the Trap Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots
SGD over Diagonal Linear Networks Implicit bias, Large Stepsizes and Edge of Stability
Shape Nonrigid Kinematics SNK A ZeroShot Method for NonRigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction
SHAPIQ Unified Approximation of anyorder Shapley Interactions
Shared Adversarial Unlearning Backdoor Mitigation by Unlearning Shared Adversarial Examples
SharpnessAware Minimization Leads to LowRank Features
Sharp Bounds for Generalized Causal Sensitivity Analysis
Sharp Calibrated Gaussian Processes
Sharp Recovery Thresholds of Tensor PCA Spectral Algorithms
Sheaf Hypergraph Networks
SheetCopilot Bringing Software Productivity to the Next Level through Large Language Models
ShiftAddViT Mixture of Multiplication Primitives Towards Efficient Vision Transformer
SHOT Suppressing the Hessian along the Optimization Trajectory for GradientBased MetaLearning
Should Underparameterized Student Networks Copy or Average Teacher Weights
Should We Learn Most Likely Functions or Parameters
Similarity, Compression and Local Steps Three Pillars of Efficient Communications for Distributed Variational Inequalities
Similaritybased cooperative equilibrium
SimMMDG A Simple and Effective Framework for Multimodal Domain Generalization
Simple, Scalable and Effective Clustering via OneDimensional Projections
Simple and Asymmetric Graph Contrastive Learning without Augmentations
Simple and Controllable Music Generation
Simplicity Bias in 1Hidden Layer Neural Networks
Simplifying and Empowering Transformers for LargeGraph Representations
Simplifying Neural Network Training Under Class Imbalance
Simultaneous embedding of multiple attractor manifolds in a recurrent neural network using constrained gradient optimization
SingleCall Stochastic Extragradient Methods for Structured Nonmonotone Variational Inequalities Improved Analysis under Weaker Conditions
SinglePass Pivot Algorithm for Correlation Clustering. Keep it simple!
SingleStage Visual Query Localization in Egocentric Videos
Sketching Algorithms for Sparse Dictionary Learning PTAS and Turnstile Streaming
Sketchy Memoryefficient Adaptive Regularization with Frequent Directions
SLaM StudentLabel Mixing for Distillation with Unlabeled Examples
SLIBONet Floorplan Reconstruction via Slicing Box Representation with Local Geometry Regularization
Slimmed Asymmetrical Contrastive Learning and Cross Distillation for Lightweight Model Training
SLM A Smoothed FirstOrder Lagrangian Method for Structured Constrained Nonconvex Optimization
Slotguided Volumetric Object Radiance Fields
Small batch deep reinforcement learning
Small TotalCost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness
SmooSeg Smoothness Prior for Unsupervised Semantic Segmentation
Smooth, exact rotational symmetrization for deep learning on point clouds
<a href=http://doc.flyingfry.cc/NIPS2023/poster/SmoothHess_ReLU_Network_Feature_Interactions_via_Stein's_Lemma.pdf>SmoothHess ReLU Network Feature Interactions via Stein's Lemma
Smooth Flipping Probability for Differential Private Sign Random Projection Methods
SnapFusion TexttoImage Diffusion Model on Mobile Devices within Two Seconds
SNAP SelfSupervised Neural Maps for Visual Positioning and Semantic Understanding
SNEkhorn Dimension Reduction with Symmetric Entropic Affinities
SOAR Improved Indexing for Approximate Nearest Neighbor Search
Social Motion Prediction with Cognitive Hierarchies
SOC SemanticAssisted Object Cluster for Referring Video Object Segmentation
SODA Robust Training of TestTime Data Adaptors
Softmax Output Approximation for Activation MemoryEfficient Training of Attentionbased Networks
SoftUnification in Deep Probabilistic Logic
Solving a Class of NonConvex Minimax Optimization in Federated Learning
Solving Inverse Physics Problems with Score Matching
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models
SOL Samplingbased Optimal Linear bounding of arbitrary scalar functions
Sorting with Predictions
SoTTA Robust TestTime Adaptation on Noisy Data Streams
SPACE Singleround Participant Amalgamation for Contribution Evaluation in Federated Learning
SparseProp Efficient EventBased Simulation and Training of Sparse Recurrent Spiking Neural Networks
Sparse Deep Learning for Time Series Data Theory and Applications
Sparse Modular Activation for Efficient Sequence Modeling
Sparse Parameterization for Epitomic Dataset Distillation
SparsityPreserving Differentially Private Training of Large Embedding Models
Spatially Resolved Gene Expression Prediction from Histology Images via Bimodal Contrastive Learning
SpatialRank Urban Event Ranking with NDCG Optimization on Spatiotemporal Data
SpatioAngular Convolutions for Superresolution in Diffusion MRI
SPA A Graph Spectral Alignment Perspective for Domain Adaptation
Spectral CoDistillation for Personalized Federated Learning
Spectral Entrywise Matrix Estimation for LowRank Reinforcement Learning
Spectral Evolution and Invariance in Linearwidth Neural Networks
Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts
SpecTr Fast Speculative Decoding via Optimal Transport
Speculative Decoding with Big Little Decoder
Spikedriven Transformer
Spiking PointNet Spiking Neural Networks for Point Clouds
Spontaneous symmetry breaking in generative diffusion models
SPQR Controlling Qensemble Independence with Spiked Random Model for Reinforcement Learning
SPRING Studying Papers and Reasoning to play Games
Spuriosity Didnt Kill the Classifier Using Invariant Predictions to Harness Spurious Features
SQ Lower Bounds for Learning Mixtures of Linear Classifiers
SQ Lower Bounds for NonGaussian Component Analysis with Weaker Assumptions
Stabilitypenaltyadaptive followtheregularizedleader Sparsity, gamedependency, and bestofbothworlds
Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm
Stability Guarantees for Feature Attributions with Multiplicative Smoothing
Stability of Random Forests and Coverage of RandomForest Prediction Intervals
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints
Stabilizing the Optimization of Neural Signed Distance Functions and Finer Shape Representation
StableFDG Style and Attention Based Learning for Federated Domain Generalization
StableRep Synthetic Images from TexttoImage Models Make Strong Visual Representation Learners
Stable and lowprecision training for largescale visionlanguage models
Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures
StarShaped Denoising Diffusion Probabilistic Models
State2Explanation ConceptBased Explanations to Benefit Agent Learning and User Understanding
StateAction SimilarityBased Representations for OffPolicy Evaluation
StateMask Explaining Deep Reinforcement Learning through State Mask
Statespace models with layerwise nonlinearity are universal approximators with exponential decaying memory
State Regularized Policy Optimization on Data with Dynamics Shift
Static and Sequential Malicious Attacks in the Context of Selective Forgetting
Statistically Valid Variable Importance Assessment through Conditional Permutations
Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks
Statistical and Computational Tradeoff in MultiAgent MultiArmed Bandits
Statistical Insights into HSIC in High Dimensions
Statistical Knowledge Assessment for Large Language Models
Statistical Limits of Adaptive Linear Models LowDimensional Estimation and Inference
Stochastic Approximation Algorithms for Systems of Interacting Particles
Stochastic Approximation Approaches to Group Distributionally Robust Optimization
Stochastic Collapse How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks
Stochastic Distributed Optimization under Average Secondorder Similarity Algorithms and Analysis
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths
STORM Efficient Stochastic Transformer based World Models for Reinforcement Learning
Strategic Apple Tasting
Strategic Behavior in Twosided Matching Markets with Predictionenhanced Preferenceformation
Strategic Classification under Unknown Personalized Manipulation
Strategic Data Sharing between Competitors
Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows
Strategyproof Voting under Correlated Beliefs
STREAMER Streaming Representation Learning and Event Segmentation in a Hierarchical Manner
Streaming Algorithms and Lower Bounds for Estimating Correlation Clustering Cost
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition
StreamNet MemoryEfficient Streaming Tiny Deep Learning Inference on the Microcontroller
Strong and Precise Modulation of Human Percepts via Robustified ANNs
Structural Pruning for Diffusion Models
Structured Federated Learning through Clustered Additive Modeling
Structured NeuralPI Control with EndtoEnd Stability and Output Tracking Guarantees
Structured Neural Networks for Density Estimation and Causal Inference
Structured Prediction with Stronger Consistency Guarantees
Structured Semidefinite Programming for Recovering Structured Preconditioners
Structured State Space Models for InContext Reinforcement Learning
Structured Voronoi Sampling
Structure from Duplicates Neural Inverse Graphics from a Pile of Objects
Structure Learning with Adaptive Random Neighborhood Informed MCMC
Structure of universal formulas
STXD Structural and Temporal CrossModal Distillation for MultiView 3D Object Detection
StyleDrop TexttoImage Synthesis of Any Style
StyleGAN knows Normal, Depth, Albedo, and More
StyleTTS 2 Towards HumanLevel TexttoSpeech through Style Diffusion and Adversarial Training with Large Speech Language Models
SubclassDominant Label Noise A Counterexample for the Success of Early Stopping
Subjectdriven TexttoImage Generation via Apprenticeship Learning
Suboptimality of the Naive Mean Field approximation for proportional highdimensional Linear Regression
SUBP Soft Uniform Block Pruning for 1timesN Sparse CNNs Multithreading Acceleration
SuccessorPredecessor Intrinsic Exploration
Suggesting Variable Order for Cylindrical Algebraic Decomposition via Reinforcement Learning
SupplySide Equilibria in Recommender Systems
Supported Value Regularization for Offline Reinforcement Learning
Survival Permanental Processes for Survival Analysis with TimeVarying Covariates
SutraNets Subseries Autoregressive Networks for LongSequence, Probabilistic Forecasting
SwapPrompt TestTime Prompt Adaptation for VisionLanguage Models
Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration
Swarm Reinforcement Learning for Adaptive Mesh Refinement
SwiFT Swin 4D fMRI Transformer
Switching Autoregressive Lowrank Tensor Models
Switching Temporary Teachers for SemiSupervised Semantic Segmentation
Symbolic Discovery of Optimization Algorithms
SymbolLLM Leverage Language Models for Symbolic System in Visual Human Activity Reasoning
SyncDiffusion Coherent Montage via Synchronized Joint Diffusions
SyncTREE Fast Timing Analysis for Integrated Circuit Design through a Physicsinformed Treebased Graph Neural Network
SynthetictoReal Pose Estimation with Geometric Reconstruction
Synthetic Combinations A Causal Inference Framework for Combinatorial Interventions
Synthetic Experience Replay
Systematic Visual Reasoning through ObjectCentric Relational Abstraction
S^3 Increasing GPU Utilization during Generative Inference for Higher Throughput
TabMT Generating tabular data with masked transformers
Tackling HeavyTailed Rewards in Reinforcement Learning with Function Approximation Minimax Optimal and InstanceDependent Regret Bounds
Tailoring SelfAttention for Graph via Rooted Subtrees
Taking the neural sampling code very seriously A datadriven approach for evaluating generative models of the visual system
Tame a Wild Camera IntheWild Monocular Camera Calibration
Taming Local Effects in Graphbased Spatiotemporal Forecasting
Tanh Works Better with Asymmetry
Tanimoto Random Features for Scalable Molecular Machine Learning
TART A plugandplay Transformer module for taskagnostic reasoning
Taskaware Distributed Source Coding under Dynamic Bandwidth
Taskaware world model learning with meta weighting via bilevel optimization
TaskMet Taskdriven Metric Learning for Model Learning
TaskRobust PreTraining for WorstCase Downstream Adaptation
Taylor TDlearning
TD Convergence An Optimization Perspective
TeamPSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning
Templatefree Articulated Neural Point Clouds for Reposable View Synthesis
TempME Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery
Temporally Disentangled Representation Learning under Unknown Nonstationarity
Temporal Causal Mediation through a Point Process Direct and Indirect Effects of Healthcare Interventions
Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes
Temporal Continual Learning with Prior Compensation for Human Motion Prediction
Temporal Dynamic Quantization for Diffusion Models
Temporal Robustness against Data poisoning
Tempo Adaptation in Nonstationary Reinforcement Learning
TensorNet Cartesian Tensor Representations for Efficient Learning of Molecular Potentials
Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples
Testtime Adaptation of Discriminative Models via Diffusion Generative Feedback
TestTime Amendment with a Coarse Classifier for FineGrained Classification
TestTime Distribution Normalization for Contrastively Learned Visuallanguage Models
Testtime Training for Matchingbased Video Object Segmentation
TexQ Zeroshot Network Quantization with Texture Feature Distribution Calibration
textbfA^2textbfCiD^2 Accelerating Asynchronous Communication in Decentralized Deep Learning
TextDiffuser Diffusion Models as Text Painters
textttTACO Temporal Latent ActionDriven Contrastive Loss for Visual Reinforcement Learning
Textually Pretrained Speech Language Models
Text Alignment Is An Efficient Unified Model for Massive NLP Tasks
Text Promptable Surgical Instrument Segmentation with VisionLanguage Models
TFLEX Temporal FeatureLogic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph
Theoretically Guaranteed Bidirectional Data Rectification for Robust Sequential Recommendation
Theoretical Analysis of the Inductive Biases in Deep Convolutional Networks
The Adversarial Consistency of Surrogate Risks for Binary Classification
The Bayesian Stability Zoo
The Benefits of Being Distributional SmallLoss Bounds for Reinforcement Learning
The Best of Both Worlds in Network Population Games Reaching Consensus and Convergence to Equilibrium
The CLIP Model is Secretly an ImagetoPrompt Converter
The Contextual Lasso Sparse Linear Models via Deep Neural Networks
The Crucial Role of Normalization in SharpnessAware Minimization
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
The Distortion of Binomial Voting Defies Expectation
The DoubleEdged Sword of Implicit Bias Generalization vs. Robustness in ReLU Networks
The emergence of clusters in selfattention dynamics
The Emergence of Essential Sparsity in Large Pretrained Models The Weights that Matter
The expressive power of pooling in Graph Neural Networks
The Gain from Ordering in Online Learning
The geometry of hidden representations of large transformer models
The Grand Illusion The Myth of Software Portability and Implications for ML Progress
The Graph Pencil Method Mapping Subgraph Densities to Stochastic Block Models
The Impact of Positional Encoding on Length Generalization in Transformers
The Learnability of InContext Learning
<a href=http://doc.flyingfry.cc/NIPS2023/poster/The_MemoryPerturbation_Equation_Understanding_Model's_Sensitivity_to_Data.pdf>The MemoryPerturbation Equation Understanding Model's Sensitivity to Data
The noise level in linear regression with dependent data
The probability flow ODE is provably fast
The Quantization Model of Neural Scaling
The RankReduced Kalman Filter Approximate DynamicalLowRank Filtering In High Dimensions
The Rise of AI Language Pathologists Exploring Twolevel Prompt Learning for Fewshot Weaklysupervised Whole Slide Image Classification
The Shaped Transformer Attention Models in the Infinite DepthandWidth Limit
The Simplicity Bias in MultiTask RNNs Shared Attractors, Reuse of Dynamics, and Geometric Representation
The svalue evaluating stability with respect to distributional shifts
The TargetCharging Technique for Privacy Analysis across Interactive Computations
The Transient Nature of Emergent InContext Learning in Transformers
The Tunnel Effect Building Data Representations in Deep Neural Networks
The Utility of Even if Semifactual Explanation to Optimise Positive Outcomes
Thinker Learning to Plan and Act
Thin and deep Gaussian processes
This Looks Like Those Illuminating Prototypical Concepts Using Multiple Visualizations
ThreeWay TradeOff in MultiObjective Learning Optimization, Generalization and ConflictAvoidance
Three Towers Flexible Contrastive Learning with Pretrained Image Models
Thrust Adaptively Propels Large Language Models with External Knowledge
TIESMerging Resolving Interference When Merging Models
Tight Bounds for Volumetric Spanners and Applications
TimeIndependent InformationTheoretic Generalization Bounds for SGLD
TimeReversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value
Timeuniform confidence bands for the CDF under nonstationarity
Time Series as Images Vision Transformer for Irregularly Sampled Time Series
Time Series Kernels based on Nonlinear Vector AutoRegressive Delay Embeddings
TMTVIS Taxonomyaware Multidataset Joint Training for Video Instance Segmentation
TOA Taskoriented Active VQA
TokenScaled Logit Distillation for Ternary Weight Generative Language Models
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Tools_for_Verifying_Neural_Models'_Training_Data.pdf>Tools for Verifying Neural Models' Training Data
TopAmbiguity Samples Matter Understanding Why Deep Ensemble Works in Selective Classification
Topological Obstructions and How to Avoid Them
Topological RANSAC for instance verification and retrieval without finetuning
TopologyAware Uncertainty for Image Segmentation
TopoSRL Topology preserving selfsupervised Simplicial Representation Learning
TopP&R Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models
Towards Accelerated Model Training via Bayesian Data Selection
Towards Anytime Classification in EarlyExit Architectures by Enforcing Conditional Monotonicity
Towards a fuller understanding of neurons with Clustered Compositional Explanations
Towards A Richer 2D Understanding of Hands at Scale
Towards a Unified Analysis of Kernelbased Methods Under Covariate Shift
Towards a Unified Framework of Contrastive Learning for Disentangled Representations
Towards Better Dynamic Graph Learning New Architecture and Unified Library
Towards Characterizing the Firstorder Query Complexity of Learning Approximate Nash Equilibria in Zerosum Matrix Games
Towards Combinatorial Generalization for Catalysts A KohnSham ChargeDensity Approach
Towards Consistent Video Editing with TexttoImage Diffusion Models
Towards DataAgnostic Pruning At Initialization What Makes a Good Sparse Mask
Towards DataAlgorithm Dependent Generalization a Case Study on Overparameterized Linear Regression
Towards DistributionAgnostic Generalized Category Discovery
Towards Efficient and Accurate Winograd Convolution via Full Quantization
Towards Efficient Image Compression Without Autoregressive Models
Towards Efficient PreTrained Language Model via Feature Correlation Distillation
Towards Evaluating Transferbased Attacks Systematically, Practically, and Fairly
Towards Foundation Models for Scientific Machine Learning Characterizing Scaling and Transfer Behavior
Towards Free Data Selection with GeneralPurpose Models
Towards Generic SemiSupervised Framework for Volumetric Medical Image Segmentation
Towards Higher Ranks via Adversarial Weight Pruning
Towards Hybridgrained Feature Interaction Selection for Deep Sparse Network
Towards Labelfree Scene Understanding by Vision Foundation Models
Towards Label Position Bias in Graph Neural Networks
Towards Lastlayer Retraining for Group Robustness with Fewer Annotations
Towards Optimal Caching and Model Selection for Large Model Inference
Towards Optimal Effective Resistance Estimation
Towards Personalized Federated Learning via Heterogeneous Model Reassembly
Towards robust and generalizable representations of extracellular data using contrastive learning
Towards SelfInterpretable GraphLevel Anomaly Detection
Towards SemiStructured Automatic ICD Coding via Treebased Contrastive Learning
Towards Stable Backdoor Purification through Feature Shift Tuning
Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities
Towards Unbounded Machine Unlearning
Towards Understanding the Dynamics of GaussianStein Variational Gradient Descent
Toward Better PACBayes Bounds for Uniformly Stable Algorithms
Toward ReIdentifying Any Animal
Toward Understanding Generative Data Augmentation
To Repeat or Not To Repeat Insights from Scaling LLM under TokenCrisis
To Stay or Not to Stay in the Pretrain Basin Insights on Ensembling in Transfer Learning
Tracking Most Significant Shifts in Nonparametric Contextual Bandits
Tradeoff Between Efficiency and Consistency for Removalbased Explanations
Tradingoff price for data quality to achieve fair online allocation
Trainingfree Diffusion Model Adaptation for VariableSized TexttoImage Synthesis
Training biologically plausible recurrent neural networks on cognitive tasks with longterm dependencies
Training ChainofThought via LatentVariable Inference
Training EnergyBased Normalizing Flow with ScoreMatching Objectives
Training Fully Connected Neural Networks is existsmathbbRComplete
Training Neural Networks is NPHard in Fixed Dimension
Training neural operators to preserve invariant measures of chaotic attractors
Training on Foveated Images Improves Robustness to Adversarial Attacks
Training Private Models That Know What They Dont Know
Training Transformers with 4bit Integers
Training Transitive and Commutative Multimodal Transformers with LoReTTa
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Train_'n_Trade_Foundations_of_Parameter_Markets.pdf>Train 'n Trade Foundations of Parameter Markets
Train Faster, Perform Better Modular Adaptive Training in OverParameterized Models
Train Hard, Fight Easy Robust Meta Reinforcement Learning
Train Once and Explain Everywhere Pretraining Interpretable Graph Neural Networks
Trajectory Alignment Understanding the Edge of Stability Phenomenon via Bifurcation Theory
Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings
Transfer Learning with Affine Model Transformation
Transformed LowRank Parameterization Can Help Robust Generalization for Tensor Neural Networks
Transformerbased Planning for Symbolic Regression
Transformers are uninterpretable with myopic methods a case study with bounded Dyck grammars
Transformers learn through gradual rank increase
Transformers learn to implement preconditioned gradient descent for incontext learning
Transformers over Directed Acyclic Graphs
Transformer as a hippocampal memory consolidation model based on NMDARinspired nonlinearity
TransHP Image Classification with Hierarchical Prompting
Transitivity Recovering Decompositions Interpretable and Robust FineGrained Relationships
Transportability for Bandits with Data from Different Environments
TreeRings Watermarks Invisible Fingerprints for Diffusion Images
TRIAGE Characterizing and auditing training data for improved regression
Trial matching capturing variability with dataconstrained spiking neural networks
Triangulation Residual Loss for Dataefficient 3D Pose Estimation
Triple Eagle Simple, Fast and Practical BudgetFeasible Mechanisms
TriRE A MultiMechanism Learning Paradigm for Continual Knowledge Retention and Promotion
TrojLLM A Blackbox Trojan Prompt Attack on Large Language Models
Truly ScaleEquivariant Deep Nets with Fourier Layers
Truncated Affinity Maximization Oneclass Homophily Modeling for Graph Anomaly Detection
Truncating Trajectories in Monte Carlo Policy Evaluation an Adaptive Approach
Trust RegionBased Safe Distributional Reinforcement Learning for Multiple Constraints
Trust Your nabla Gradientbased Intervention Targeting for Causal Discovery
Tuning Multimode Tokenlevel Prompt Alignment across Modalities
TwoStage Learning to Defer with Multiple Experts
TwoStage Predict+Optimize for MILPs with Unknown Parameters in Constraints
Two Heads are Better Than One A Simple Exploration Framework for Efficient MultiAgent Reinforcement Learning
Two Sides of One Coin the Limits of Untuned SGD and the Power of Adaptive Methods
Two Sides of The Same Coin Bridging Deep Equilibrium Models and Neural ODEs via Homotopy Continuation
TypetoTrack Retrieve Any Object via Promptbased Tracking
UE4NeRFNeural Radiance Field for RealTime Rendering of LargeScale Scene
UltraRE Enhancing RecEraser for Recommendation Unlearning via Error Decomposition
Unbalanced Lowrank Optimal Transport Solvers
Unbiased Compression Saves Communication in Distributed Optimization When and How Much
Unbiased constrained sampling with SelfConcordant Barrier Hamiltonian Monte Carlo
Unbiased learning of deep generative models with structured discrete representations
Unbounded Differentially Private Quantile and Maximum Estimation
UncertaintyAware Alignment Network for CrossDomain VideoText Retrieval
UncertaintyAware Instance Reweighting for OffPolicy Learning
Uncertainty Estimation for Safetycritical Scene Segmentation via Finegrained Reward Maximization
Uncertainty Quantification via Neural Posterior Principal Components
Unconstrained Dynamic Regret via Sparse Coding
Uncoupled and Convergent Learning in TwoPlayer ZeroSum Markov Games with Bandit Feedback
Uncovering and Quantifying Social Biases in Code Generation
Uncovering Meanings of Embeddings via Partial Orthogonality
Uncovering Prototypical Knowledge for Weakly OpenVocabulary Semantic Segmentation
Understanding, Predicting and Better Resolving QValue Divergence in OfflineRL
Understanding and Addressing the Pitfalls of Bisimulationbased Representations in Offline Reinforcement Learning
Understanding and Improving Ensemble Adversarial Defense
Understanding and Improving Feature Learning for OutofDistribution Generalization
Understanding and Mitigating Copying in Diffusion Models
Understanding Contrastive Learning via Distributionally Robust Optimization
Understanding Deep Gradient Leakage via Inversion Influence Functions
Understanding FewShot Learning Measuring Task Relatedness and Adaptation Difficulty via Attributes
Understanding How Consistency Works in Federated Learning via Stagewise Relaxed Initialization
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers
Understanding the detrimental classlevel effects of data augmentation
Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry
Understanding the Limitations of Deep Models for Molecular property prediction Insights and Solutions
Undirected Probabilistic Model for Tensor Decomposition
Uni3DETR Unified 3D Detection Transformer
UniControlNet AllinOne Control to TexttoImage Diffusion Models
UniControl A Unified Diffusion Model for Controllable Visual Generation In the Wil
Unified 3D Segmenter As Prototypical Classifiers
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via fDifferential Privacy
Unified Lower Bounds for Interactive Highdimensional Estimation under Information Constraints
Unified OffPolicy Learning to Rank a Reinforcement Learning Perspective
Unified SegmenttoSegment Framework for Simultaneous Sequence Generation
UniforminTime Wasserstein Stability Bounds for Noisy Stochastic Gradient Descent
Uniform Convergence with SquareRoot Lipschitz Loss
Unifying GANs and ScoreBased Diffusion as Generative Particle Models
UniPC A Unified PredictorCorrector Framework for Fast Sampling of Diffusion Models
UniTSFace Unified Threshold Integrated SampletoSample Loss for Face Recognition
UniT A Unified Look at Certified Robust Training against Text Adversarial Perturbation
Universality and Limitations of Prompt Tuning
Universality laws for Gaussian mixtures in generalized linear models
Universal Gradient Descent Ascent Method for NonconvexNonconcave Minimax Optimization
Universal Prompt Tuning for Graph Neural Networks
Unleashing the Full Potential of Product Quantization for LargeScale Image Retrieval
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift
Unleashing the Power of Randomization in Auditing Differentially Private ML
Unleash the Potential of Image Branch for Crossmodal 3D Object Detection
Unlimiformer LongRange Transformers with Unlimited Length Input
Unlocking Deterministic Robustness Certification on ImageNet
Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization
UNSSOR Unsupervised Neural Speech Separation by Leveraging Overdetermined Training Mixtures
Unsupervised Anomaly Detection with Rejection
Unsupervised Behavior Extraction via Random Intent Priors
Unsupervised Graph Neural Architecture Search with Disentangled SelfSupervision
Unsupervised Image Denoising with Score Function
Unsupervised Learning for Solving the Travelling Salesman Problem
Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera
Unsupervised Polychromatic Neural Representation for CT Metal Artifact Reduction
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Unsupervised_ProteinLigand_Binding_Energy_Prediction_via_Neural_Euler's_Rotation_Equation.pdf>Unsupervised ProteinLigand Binding Energy Prediction via Neural Euler's Rotation Equation
Unsupervised Semantic Correspondence Using Stable Diffusion
Unsupervised Video Domain Adaptation for Action Recognition A Disentanglement Perspective
UPDP Unsupervised Prompt Learning for Data PreSelection with VisionLanguage Models
UPNeRF Unconstrained Pose PriorFree Neural Radiance Fiel
Use perturbations when learning from explanations
Using Imperfect Surrogates for Downstream Inference Designbased Supervised Learning for Social Science Applications of Large Language Models
Utilitarian Algorithm Configuration
VanillaNet the Power of Minimalism in Deep Learning
varepsilonfractional core stability in Hedonic Games
VarianceReduced Gradient Estimation via NoiseReuse in Online Evolution Strategies
Variational Annealing on Graphs for Combinatorial Optimization
Variational Gaussian processes for linear inverse problems
Variational Gaussian Processes with Decoupled Conditionals
Variational Imbalanced Regression Fair Uncertainty Quantification via Probabilistic Smoothing
Variational Inference with Gaussian Score Matching
Variational Monte Carlo on a Budget Finetuning pretrained Neural Wavefunctions
Variational Weighting for Kernel Density Ratios
VAST A VisionAudioSubtitleText OmniModality Foundation Model and Dataset
VCC Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens
VeriX Towards Verified Explainability of Deep Neural Networks
Versatile EnergyBased Probabilistic Models for High Energy Physics
ViCANeRF ViewConsistencyAware 3D Editing of Neural Radiance Fields
VideoComposer Compositional Video Synthesis with Motion Controllability
VideoMined Task Graphs for Keystep Recognition in Instructional Videos
Video Dynamics Prior An Internal Learning Approach for Robust Video Enhancements
Video Prediction Models as Rewards for Reinforcement Learning
VillanDiffusion A Unified Backdoor Attack Framework for Diffusion Models
VInFoR A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs
VisionLLM Large Language Model is also an OpenEnded Decoder for VisionCentric Tasks
ViSt3D Video Stylization with 3D CNN
Visual Instruction Inversion Image Editing via Image Prompting
Visual Programming for StepbyStep TexttoImage Generation and Evaluation
VLATTACK Multimodal Adversarial Attacks on VisionLanguage Tasks via Pretrained Models
Vocabularyfree Image Classification
VOCE Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning
Voicebox TextGuided Multilingual Universal Speech Generation at Scale
Volume Feature Rendering for Fast Neural Radiance Field Reconstruction
VPGTrans Transfer Visual Prompt Generator across LLMs
VPP Efficient Conditional 3D Generation via VoxelPoint Progressive Representation
VRA Variational Rectified Activation for Outofdistribution Detection
WalkLM A Uniform Language Model Finetuning Framework for Attributed Graph Embedding
Wasserstein distributional robustness of neural networks
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies
Waypoint Transformer Reinforcement Learning via Supervised Learning with Intermediate Targets
WeaklySupervised AudioVisual Segmentation
WeaklySupervised Concealed Object Segmentation with SAMbased Pseudo Labeling and Multiscale Feature Grouping
Weakly Coupled Deep QNetworks
Weakly Supervised 3D Openvocabulary Segmentation
Weighted ROC Curve in Cost Space Extending AUC to CostSensitive Learning
<a href=http://doc.flyingfry.cc/NIPS2023/poster/Weitzman's_Rule_for_Pandora's_Box_with_Correlations.pdf>Weitzman's Rule for Pandora's Box with Correlations
Whats Left Concept Grounding with LogicEnhanced Foundation Models
What can a Single Attention Layer Learn A Study Through the Random Features Lens
What Can We Learn from Unlearnable Datasets
What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners
What Do Deep Saliency Models Learn about Visual Attention
What functions can Graph Neural Networks compute on random graphs The role of Positional Encoding
What is Flagged in Uncertainty Quantification Latent Density Models for Uncertainty Categorization
What is the Inductive Bias of Flatness Regularization A Study of Deep Matrix Factorization Models
What Knowledge Gets Distilled in Knowledge Distillation
What Makes Good Examples for Visual InContext Learning
What Truly Matters in Trajectory Prediction for Autonomous Driving
What You See is What You Read Improving TextImage Alignment Evaluation
When are ensembles really effective
When can RegressionAdjusted Control Variate Help Rare Events, Sobolev Embedding and Minimax Optimality
When Can We Track Significant Preference Shifts in Dueling Bandits
When Does ConfidenceBased Cascade Deferral Suffice
When Do Graph Neural Networks Help with Node Classification Investigating the Homophily Principle on Node Distinguishability
When is Agnostic Reinforcement Learning Statistically Tractable
When Visual Prompt Tuning Meets SourceFree Domain Adaptive Semantic Segmentation
Where2Explore Fewshot Affordance Learning for Unseen Novel Categories of Articulated Objects
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence
Where Did I Come From Origin Attribution of AIGenerated Images
WhiteBox Transformers via Sparse Rate Reduction
Why Did This Model Forecast This Future InformationTheoretic Saliency for Counterfactual Explanations of Probabilistic Regression Models
Why Does SharpnessAware Minimization Generalize Better Than SGD
Why Not Looking backward A Robust TwoStep Method to Automatically Terminate Bayesian Optimization
Wide Neural Networks as Gaussian Processes Lessons from Deep Equilibrium Models
WindowBased Distribution Shift Detection for Deep Neural Networks
WinnerTakeAll Column Row Sampling for Memory Efficient Adaptation of Language Model
Winner Takes It All Training Performant RL Populations for Combinatorial Optimization
Worstcase Performance of Popular Approximate Nearest Neighbor Search Implementations Guarantees and Limitations
XAGen 3D Expressive Human Avatars Generation
xTrimoGene An Efficient and Scalable Representation Learner for SingleCell RNASeq Data
Your representations are in the network composable and parallel adaptation for large scale models
You Only Condense Once Two Rules for Pruning Condensed Datasets
ZeroOne Laws of Graph Neural Networks
ZeroRegret Performative Prediction Under Inequality Constraints
ZeroShot Anomaly Detection via Batch Normalization
Zeroshot Visual Relation Detection via Composite Visual Cues from Large Language Models
Zerosum Polymatrix Markov Games Equilibrium Collapse and Efficient Computation of Nash Equilibria
ZerothOrder Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization
ZipLM InferenceAware Structured Pruning of Language Models