ICML 2025 Accepted Papers

The full list of 3,333 papers accepted at ICML 2025 (International Conference on Machine Learning). Click any title for details, similar papers, and links to the original source. You can also search these papers by meaning, not just keywords.

Poster: 2,988Spotlight: 225Oral: 120

Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks SafetySpotlight
Best Subset Selection: Optimal Pursuit for Feature Selection and EliminationPoster
Best of Both Worlds: Regret Minimization versus Minimax PlayPoster
Better to Teach than to Give: Domain Generalized Semantic Segmentation via Agent Queries with Diffusion Model GuidanceSpotlight
Beyond Bradley-Terry Models: A General Preference Model for Language Model AlignmentPoster
Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed LearningPoster
Beyond Confidence: Exploiting Homogeneous Pattern for Semi-Supervised Semantic SegmentationPoster
Beyond Cropped Regions: New Benchmark and Corresponding Baseline for Chinese Scene Text Retrieval in Diverse LayoutsPoster
Beyond Entropy: Region Confidence Proxy for Wild Test-Time AdaptationPoster
Beyond Induction Heads: In-Context Meta Learning Induces Multi-Phase Circuit EmergencePoster
Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device LearningPoster
Beyond Message Passing: Neural Graph Pattern MachinePoster
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of SparsityPoster
Beyond One-Hot Labels: Semantic Mixing for Model CalibrationPoster
Beyond Self-Interest: How Group Strategies Reshape Content Creation in Recommendation Platforms?Poster
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General GraphsOral
Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health PredictionsPoster
Beyond Task-Specific Reasoning: A Unified Conditional Generative Framework for Abstract Visual ReasoningPoster
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PCPoster
Beyond Topological Self-Explainable GNNs: A Formal Explainability PerspectivePoster
Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning DynamicsPoster
Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model FusionSpotlight
Bi-perspective Splitting Defense: Achieving Clean-Seed-Free Backdoor SecurityPoster
BiAssemble: Learning Collaborative Affordance for Bimanual Geometric AssemblyPoster
BiMaCoSR: Binary One-Step Diffusion Model Leveraging Flexible Matrix Compression for Real Super-ResolutionPoster
BiMark: Unbiased Multilayer Watermarking for Large Language ModelsPoster
Bifurcate then Alienate: Incomplete Multi-view Clustering via Coupled Distribution Learning with Linear OverheadPoster
Binary Hypothesis Testing for Softmax Models and Leverage Score ModelsPoster
BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching ModelsPoster
Bivariate Causal Discovery with Proxy Variables: Integral Solving and BeyondPoster
Blink of an eye: a simple theory for feature localization in generative modelsOral
BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM InferencePoster
BoA: Attention-aware Post-training Quantization without BackpropagationPoster
Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority GenerationPoster
Boosting Adversarial Robustness with CLAT: Criticality Leveraged Adversarial TrainingPoster
Boosting Masked ECG-Text Auto-Encoders as Discriminative LearnersPoster
Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between SamplesPoster
Boosting Protein Graph Representations through Static-Dynamic FusionPoster
Boosting Virtual Agent Learning and Reasoning: A Step-Wise, Multi-Dimensional, and Generalist Reward Model with BenchmarkPoster
Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema MatchingPoster
BounDr.E: Predicting Drug-likeness via Biomedical Knowledge Alignment and EM-like One-Class Boundary OptimizationPoster
Bounded Rationality for LLMs: Satisficing Alignment at Inference-TimePoster
BoxLM: Unifying Structures and Semantics of Medical Concepts for Diagnosis Prediction in HealthcarePoster
Branches: Efficiently Seeking Optimal Sparse Decision Trees via AO*Poster
Breaking Barriers: Combinatorial Algorithms for Non-Monotone Submodular Maximization with Sublinear Adaptivity and $1/e$ ApproximationPoster
Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series ForecastingPoster
Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander DecompositionPoster
Breaking the Barrier of Hard Samples: A Data-Centric Approach to Synthetic Data for Medical TasksPoster
Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement LearningPoster
Bridging Fairness and Efficiency in Conformal Inference: A Surrogate-Assisted Group-Clustered ApproachPoster
Bridging Layout and RTL: Knowledge Distillation based Timing PredictionSpotlight
Bridging Protein Sequences and Microscopy Images with Unified Diffusion ModelsPoster
Broadband Ground Motion Synthesis by Diffusion Model with Minimal ConditionPoster
Byzantine-Resilient Federated Alternating Gradient Descent and Minimization for Partly-Decoupled Low Rank Matrix LearningPoster
C2IQL: Constraint-Conditioned Implicit Q-learning for Safe Offline Reinforcement LearningPoster
CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model MergingPoster
CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data ImputationSpotlight
CAD-Editor: A Locate-then-Infill Framework with Automated Training Data Synthesis for Text-Based CAD EditingPoster
CALM: Consensus-Aware Localized Merging for Multi-Task LearningPoster
CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual LearningPoster
CASE-Bench: Context-Aware SafEty Benchmark for Large Language ModelsPoster
CAT Merging: A Training-Free Approach for Resolving Conflicts in Model MergingPoster
CAT: Contrastive Adversarial Training for Evaluating the Robustness of Protective Perturbations in Latent Diffusion ModelsPoster
CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and AcquisitionPoster
CERTAIN: Context Uncertainty-aware One-Shot Adaptation for Context-based Offline Meta Reinforcement LearningPoster
CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language ModelsPoster
CFPT: Empowering Time Series Forecasting through Cross-Frequency Interaction and Periodic-Aware Timestamp ModelingPoster
CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image GenerationPoster
CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous QueriesPoster
CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation ModelsPoster
CLOVER: Cross-Layer Orthogonal Vectors PruningPoster
CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial CorrelationsPoster
COExpander: Adaptive Solution Expansion for Combinatorial OptimizationPoster
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer LearningPoster
COKE: Core Kernel for More Efficient Approximation of Kernel Weights in Multiple Kernel ClusteringPoster
COMRECGC: Global Graph Counterfactual Explainer through Common RecoursePoster
COSDA: Counterfactual-based Susceptibility Risk Framework for Open-Set Domain AdaptationPoster
CPCF: A Cross-Prompt Contrastive Framework for Referring Multimodal Large Language ModelsPoster
CRANE: Reasoning with constrained LLM generationPoster
CSG-ODE: ControlSynth Graph ODE For Modeling Complex Evolution of Dynamic GraphsPoster
CSTrack: Enhancing RGB-X Tracking via Compact Spatiotemporal FeaturesPoster
CSV-Occ: Fusing Multi-frame Alignment for Occupancy Prediction with Temporal Cross State Space Model and Central Voting MechanismPoster
CUPS: Improving Human Pose-Shape Estimators with Conformalized Deep UncertaintyPoster
Ca2-VDM: Efficient Autoregressive Video Diffusion Model with Causal Generation and Cache SharingPoster
Cache Me If You Must: Adaptive Key-Value Quantization for Large Language ModelsPoster
Calibrated Language Models and How to Find Them with Label SmoothingPoster
Calibrated Physics-Informed Uncertainty QuantificationPoster
Calibrated Value-Aware Model Learning with Probabilistic Environment ModelsPoster
Calibrating Video Watch-time Predictions with Credible Prototype AlignmentPoster
Can Biologically Plausible Temporal Credit Assignment Rules Match BPTT for Neural Similarity? E-prop as an ExamplePoster
Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet ExcellencePoster
Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM CompressionPoster
Can DBNNs Robust to Environmental Noise for Resource-constrained Scenarios?Poster
Can Large Language Models Understand Intermediate Representations in Compilers?Poster
Can Transformers Learn Full Bayesian Inference in Context?Poster
Can We Predict Performance of Large Models across Vision-Language Tasks?Poster
Cannot See the Forest for the Trees: Invoking Heuristics and Biases to Elicit Irrational Choices of LLMsPoster
Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision TransformersPoster
Cape: Context-Aware Prompt Perturbation Mechanism with Differential PrivacyPoster
Capturing Temporal Dynamics in Large-Scale Canopy Tree Height EstimationPoster
Catch Your Emotion: Sharpening Emotion Perception in Multimodal Large Language ModelsSpotlight
Catching Two Birds with One Stone: Reward Shaping with Dual Random Networks for Balancing Exploration and ExploitationPoster
CateKV: On Sequential Consistency for Long-Context LLM Inference AccelerationPoster
Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and AsymptoticsPoster
Categorical Schrödinger Bridge MatchingPoster
Catoni Contextual Bandits are Robust to Heavy-tailed RewardsSpotlight
Causal Abstraction Inference under Lossy RepresentationsPoster
Causal Abstraction Learning based on the Semantic Embedding PrinciplePoster
Causal Attribution Analysis for Continuous OutcomesSpotlight
Causal Effect Identification in lvLiNGAM from Higher-Order CumulantsPoster
Causal Invariance-aware Augmentation for Brain Graph Contrastive LearningPoster
Causal Logistic Bandits with Counterfactual Fairness ConstraintsPoster
Causal-PIK: Causality-based Physical Reasoning with a Physics-Informed KernelPoster
Causality Inspired Federated Learning for OOD GeneralizationPoster
Causality-Aware Contrastive Learning for Robust Multivariate Time-Series Anomaly DetectionPoster
CellFlux: Simulating Cellular Morphology Changes via Flow MatchingPoster
Censor Dependent Variational InferencePoster
Certifiably Robust Model Evaluation in Federated Learning under Meta-Distributional ShiftsPoster
Certified Unlearning for Neural NetworksPoster
Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and FinetuningPoster
Channel Normalization for Time Series Channel IdentificationPoster
Chip Placement with Diffusion ModelsPoster
Circumventing Backdoor Space via Weight SymmetryPoster
Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Stochastic Bias and RemediesPoster
Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-TailedPoster
Closed-form Solutions: A New Perspective on Solving Differential EquationsPoster
Clustering Items through Bandit Feedback: Finding the Right Feature out of ManyPoster
Clustering Properties of Self-Supervised LearningPoster
Clustering via Self-Supervised DiffusionPoster
CoCoA-Mix: Confusion-and-Confidence-Aware Mixture Model for Context OptimizationPoster
CoMemo: LVLMs Need Image Context with Image MemoryPoster
CoPINN: Cognitive Physics-Informed Neural NetworksSpotlight
CoastalBench: A Decade-Long High-Resolution Dataset to Emulate Complex Coastal ProcessesPoster
Code-Generated Graph Representations Using Multiple LLM Agents for Material Properties PredictionPoster
CodeSync: Synchronizing Large Language Models with Dynamic Code Evolution at ScalePoster
CogMath: Assessing LLMs' Authentic Mathematical Ability from a Human Cognitive PerspectivePoster
CogReact: A Reinforced Framework to Model Human Cognitive Reaction Modulated by Dynamic InterventionPoster
Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful ContributionPoster
Collapse-Proof Non-Contrastive Self-Supervised LearningPoster
CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule GenerationPoster
Combinatorial Reinforcement Learning with Preference FeedbackPoster
Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank AdaptationPoster
CommVQ: Commutative Vector Quantization for KV Cache CompressionPoster
Communicating Activations Between Language Model AgentsPoster
Compact Matrix Quantum Group Equivariant Neural NetworksPoster
Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe MethodPoster
Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During TrainingPoster
Competing Bandits in Matching Markets via Super StabilityPoster
Competitively Consistent ClusteringPoster
Complete-Tree Space Favors Data-Efficient Link PredictionPoster
Componential Prompt-Knowledge Alignment for Domain Incremental LearningPoster
Compositional Condition Question Answering in Tabular UnderstandingPoster
Compositional Flows for 3D Molecule and Synthesis Pathway Co-designPoster
Compositional Generalization via Forced Rendering of Disentangled LatentsPoster
Compositional Scene Understanding through Inverse Generative ModelingPoster
Compressing tree ensembles through Level-wise Optimization and PruningPoster
Compute Optimal Inference and Provable Amortisation Gap in Sparse AutoencodersPoster
Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing FlowsPoster
Computing Voting Rules with Improvement FeedbackPoster
ConText: Driving In-context Learning for Text Removal and SegmentationPoster
Concentration Distribution Learning from Label DistributionsPoster
Concept Reachability in Diffusion Models: Beyond Dataset ConstraintsPoster
Concept-Based Unsupervised Domain AdaptationPoster
Concept-Centric Token Interpretation for Vector-Quantized Generative ModelsPoster
Concurrent Reinforcement Learning with Aggregated States via Randomized Least Squares Value IterationPoster
Conditional Diffusion Model with Nonlinear Data Transformation for Time Series ForecastingPoster
Conditioning Diffusions Using Malliavin CalculusPoster
ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference OptimizationPoster
Confidence Difference Reflects Various Supervised Signals in Confidence-Difference ClassificationPoster
Confidential Guardian: Cryptographically Prohibiting the Abuse of Model AbstentionPoster
Conformal Anomaly Detection in Event SequencesPoster
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute ApproachPoster
Conformal Tail Risk Control for Large Language Model AlignmentPoster
Conformity Score Averaging for ClassificationPoster
Confounder-Free Continual Learning via Recursive Feature NormalizationPoster
Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and RegretPoster
Consensus Based Stochastic Optimal ControlPoster
Consensus Is All You Get: The Role of Attention in TransformersPoster
Conservative Offline Goal-Conditioned Implicit V-LearningPoster
Constant Stepsize Local GD for Logistic Regression: Acceleration by InstabilityPoster
Constrain Alignment with Sparse AutoencodersPoster
Constrained Belief Updates Explain Geometric Structures in Transformer RepresentationsPoster
Constrained Exploitability Descent: An Offline Reinforcement Learning Method for Finding Mixed-Strategy Nash EquilibriumPoster
Constrained Online Convex Optimization with Polyak Feasibility StepsPoster
Constrained Pareto Set Identification with Bandit FeedbackPoster
Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf TheoremPoster
Contextual Linear Bandits with Delay as PayoffPoster
Contextual Optimization Under Model Misspecification: A Tractable and Generalizable ApproachPoster
Contextures: Representations from ContextsPoster
Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian PerspectivePoster
Continual Reinforcement Learning by Planning with Online World ModelsSpotlight
Continuous Semi-Implicit ModelsPoster
Continuous Visual Autoregressive Generation via Score MaximizationPoster
Continuous-Time Analysis of Heavy Ball Momentum in Min-Max GamesPoster
Continuously Updating Digital Twins using Large Language ModelsPoster
Contour Integration Underlies Human-Like VisionPoster
Contract Design Under Approximate Best ResponsesPoster
Contradiction Retrieval via Contrastive Learning with SparsityPoster
Contrastive Learning with Simplicial Convolutional Networks for Short-Text ClassificationPoster
Contrastive Visual Data AugmentationPoster
Control and Realism: Best of Both Worlds in Layout-to-Image without TrainingPoster
Controllable Data Generation with Hierarchical Neural RepresentationsPoster
Controlled Generation with Equivariant Variational Flow MatchingPoster
Controlling Large Language Model with Latent ActionPoster
Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe ExplorationOral
Convergence Analysis of Policy Gradient Methods with Dynamic StochasticityPoster
Convergence of Consistency Model with Multistep Sampling under General Data AssumptionsPoster
Convergence of Mean-Field Langevin Stochastic Descent-Ascent for Distributional Minimax OptimizationSpotlight
Convergence of Policy Mirror Descent Beyond Compatible Function ApproximationPoster
Convex Markov Games: A New Frontier for Multi-Agent Reinforcement LearningPoster
Cooperation of Experts: Fusing Heterogeneous Information with Large MarginPoster
Copilot Arena: A Platform for Code LLM Evaluation in the WildPoster
Core Context Aware Transformers for Long Context Language ModelingPoster
Core Knowledge Deficits in Multi-Modal Language ModelsPoster
CoreMatching: A Co-adaptive Sparse Inference Framework with Token and Neuron Pruning for Comprehensive Acceleration of Vision-Language ModelsPoster
Correlated Errors in Large Language ModelsPoster
Correlation Clustering Beyond the Pivot AlgorithmPoster
Cost-efficient Collaboration between On-device and Cloud Language ModelsPoster
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost FilteringPoster
Counterfactual Contrastive Learning with Normalizing Flows for Robust Treatment Effect EstimationPoster
Counterfactual Effect Decomposition in Multi-Agent Sequential Decision MakingPoster
Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness EvaluationPoster
Counting atoms faster: policy-based nuclear magnetic resonance pulse sequencing for atomic abundance measurementPoster
Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward LayersPoster
Cover learning for large-scale topology representationPoster
Covered Forest: Fine-grained generalization analysis of graph neural networksSpotlight
Cowpox: Towards the Immunity of VLM-based Multi-Agent SystemsPoster
Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent EnvironmentsPoster
Cross-City Latent Space Alignment for Consistency Region EmbeddingPoster
Cross-Modal Alignment via Variational Copula ModellingPoster
Cross-environment Cooperation Enables Zero-shot Multi-agent CoordinationOral
Cross-regularization: Adaptive Model Complexity through Validation GradientsPoster
Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide SequencingPoster
Curse of High Dimensionality Issue in Transformer for Long Context ModelingPoster
CurvGAD: Leveraging Curvature for Enhanced Graph Anomaly DetectionPoster
Curvature Enhanced Data Augmentation for RegressionPoster
Curvature-aware Graph Attention for PDEs on ManifoldsPoster
Customizing the Inductive Biases of Softmax Attention using Structured MatricesPoster
Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual LearningPoster
D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent SamplesPoster
DA-KD: Difficulty-Aware Knowledge Distillation for Efficient Large Language ModelsPoster
DAMA: Data- and Model-aware Alignment of Multi-modal LLMsPoster
DANCE: Dual Unbiased Expansion with Group-acquired Alignment for Out-of-distribution Graph Fairness LearningPoster
DCBM: Data-Efficient Visual Concept Bottleneck ModelsPoster
DEALing with Image Reconstruction: Deep Attentive Least SquaresPoster
DIME: Diffusion-Based Maximum Entropy Reinforcement LearningPoster
DIS-CO: Discovering Copyrighted Content in VLMs Training DataPoster
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic predictionPoster
DLP: Dynamic Layerwise Pruning in Large Language ModelsPoster
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret ResharingPoster
DMOSpeech: Direct Metric Optimization via Distilled Diffusion Model in Zero-Shot Speech SynthesisPoster
DPCore: Dynamic Prompt Coreset for Continual Test-Time AdaptationPoster
DRAG: Data Reconstruction Attack using Guided DiffusionPoster
DS-VLM: Diffusion Supervision Vision Language ModelPoster
DSBRouter: End-to-end Global Routing via Diffusion Schr\"{o}dinger BridgePoster
DTZO: Distributed Trilevel Zeroth Order Learning with Provable Non-Asymptotic ConvergencePoster
DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation ApplicationsPoster
DVI:A Derivative-based Vision Network for INRPoster
Data Mixing Optimization for Supervised Fine-Tuning of Large Language ModelsPoster
Data-Driven Selection of Instrumental Variables for Additive Nonlinear, Constant Effects ModelsPoster
Data-Juicer Sandbox: A Feedback-Driven Suite for Multimodal Data-Model Co-developmentSpotlight
Data-driven Design of Randomized Control Trials with Guaranteed Treatment EffectsPoster
DataDecide: How to Predict Best Pretraining Data with Small ExperimentsPoster
Dataflow-Guided Neuro-Symbolic Language Models for Type InferencePoster
David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-trainingPoster
De-AntiFake: Rethinking the Protective Perturbations Against Voice Cloning AttacksPoster
De-coupled NeuroGF for Shortest Path Distance Approximations on Large Terrain GraphsPoster
Decision Mixer: Integrating Long-term and Local Dependencies via Dynamic Token Selection for Decision-MakingPoster
Decision-aware Training of Spatiotemporal Forecasting Models to Select a Top-K Subset of Sites for InterventionPoster
Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy RegularizationPoster
Decomposition of Graphic Design with Unified Multimodal ModelPoster
Decoupled SGDA for Games with Intermittent Strategy CommunicationPoster
Deep Electromagnetic Structure Design Under Limited Evaluation BudgetsPoster
Deep Fuzzy Multi-view Learning for Reliable ClassificationPoster
Deep Neural Cellular Potts ModelsPoster
Deep Principal Support Vector Machines for Nonlinear Sufficient Dimension ReductionPoster
Deep Reinforcement Learning from Hierarchical Preference DesignPoster
Deep Ridgelet Transform and Unified Universality Theorem for Deep and Shallow Joint-Group-Equivariant MachinesPoster
Deep Streaming View ClusteringPoster
Deep Sturm–Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis FunctionsPoster
Deep Unsupervised Hashing via External GuidancePoster
DeepCrossAttention: Supercharging Transformer Residual ConnectionsPoster
DeepLayout: Learning Neural Representations of Circuit Placement LayoutPoster
Defending LVLMs Against Vision Attacks Through Partial-Perception SupervisionPoster
Delay-DSGN: A Dynamic Spiking Graph Neural Network with Delay Mechanisms for Evolving GraphPoster
Delta Decompression for MoE-based LLMs CompressionPoster
Demeaned Sparse: Efficient Anomaly Detection by Residual EstimatePoster
Demystifying Catastrophic Forgetting in Two-Stage Incremental Object DetectorPoster
Demystifying Singular Defects in Large Language ModelsPoster
Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy EvaluationPoster
Dendritic Localized Learning: Toward Biologically Plausible AlgorithmPoster
Density Ratio Estimation with Conditional Probability PathsPoster
Dequantified Diffusion-Schrödinger Bridge for Density Ratio EstimationPoster
Design Considerations in Offline Preference-based RLPoster
Designing Cyclic Peptides via Harmonic SDE with Atom-Bond ModelingPoster
Determinant Estimation under Memory Constraints and Neural Scaling LawsPoster
Determining Layer-wise Sparsity for Large Language Models Through a Theoretical PerspectiveSpotlight
Deterministic Sparse Fourier Transform for Continuous Signals with Frequency GapPoster
Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow ModelsPoster
DexScale: Automating Data Scaling for Sim2Real Generalizable Robot ControlPoster
DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit DifferentiationPoster
DiMa: Understanding the Hardness of Online Matching Problems via Diffusion ModelsPoster
Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schrödinger EquationPoster
Diff-MoE: Diffusion Transformer with Time-Aware and Space-Adaptive ExpertsPoster
DiffAdvMAP: Flexible Diffusion-Based Framework for Generating Natural Unrestricted Adversarial ExamplesPoster
DiffMS: Diffusion Generation of Molecules Conditioned on Mass SpectraPoster
Differentiable Quadratic Optimization For the Maximum Independent Set ProblemPoster
Differentiable Solver Search for Fast Diffusion SamplingPoster
Differentiable Structure Learning with Ancestral ConstraintsPoster
Differential Privacy Guarantees of Markov Chain Monte Carlo AlgorithmsPoster
Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and InferencePoster
Differentially Private Federated $k$-Means Clustering with Server-Side DataPoster
Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile ModelPoster
Diffuse Everything: Multimodal Diffusion Models on Arbitrary State SpacesPoster
Diffusion Counterfactual Generation with Semantic AbductionPoster
Diffusion Instruction TuningPoster
Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto SpeculationPoster
Diffusion Sampling Correction via Approximately 10 ParametersPoster
Diffusion on Language Model Encodings for Protein Sequence GenerationPoster
Diffusion-based Adversarial Purification from the Perspective of the Frequency DomainSpotlight
DiffusionVLA: Scaling Robot Foundation Models via Unified Diffusion and AutoregressionPoster
Dimension-Free Adaptive Subgradient Methods with Frequent DirectionsPoster
Dimensionality Reduction on Complex Vector Spaces for Euclidean Distance with Dynamic WeightsPoster
DipLLM: Fine-Tuning LLM for Strategic Decision-making in DiplomacyPoster
Direct Density Ratio Optimization: A Statistically Consistent Approach to Aligning Large Language ModelsPoster
Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN DiscriminatorSpotlight
Direct Motion Models for Assessing Generated VideosPoster
Direct Prediction Set Minimization via Bilevel Conformal Classifier TrainingPoster
Directed Graph Grammars for Sequence-based LearningPoster
Directly Forecasting Belief for Reinforcement Learning with DelaysPoster
Discovering Global False Negatives On the Fly for Self-supervised Contrastive LearningPoster
Discovering Latent Causal Graphs from Spatiotemporal DataPoster
Discovering Physics Laws of Dynamical Systems via Invariant Function LearningPoster
Discovering Spoofing Attempts on Language Model WatermarksPoster
Discovering a Zero (Zero-Vector Class of Machine Learning)Spotlight
Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic DimensionPoster
Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptionsPoster
Discrete and Continuous Difference of Submodular MinimizationPoster
Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference DataPoster
Discriminative Policy Optimization for Token-Level Reward ModelsPoster
Disentangled Graph Spectral Domain AdaptationPoster
Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution ShiftsPoster
Disparate Conditional Prediction in Multiclass ClassifiersPoster
Diss-l-ECT: Dissecting Graph Data with Local Euler Characteristic TransformsPoster
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMsOral
Distinguishing Cause from Effect with Causal Velocity ModelsPoster
Distributed Conformal Prediction via Message PassingPoster
Distributed Differentially Private Data Analytics via Secure SketchingPoster
Distributed Nonparametric Estimation: from Sparse to Dense Samples per TerminalPoster
Distributed Parallel Gradient Stacking(DPGS): Solving Whole Slide Image Stacking Challenge in Multi-Instance LearningPoster
Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel ManifoldPoster
Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic PerspectiveSpotlight
Distributionally Robust Active Learning for Gaussian Process RegressionPoster
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute MappingPoster
Diverse Prototypical Ensembles Improve Robustness to Subpopulation ShiftPoster
Diversified Flow Matching with Translation IdentifiabilityPoster
Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral CuriosityPoster
Divide and Conquer: Exploring Language-centric Tree Reasoning for Video Question-AnsweringPoster
Divide and Conquer: Grounding LLMs as Efficient Decision-Making Agents via Offline Hierarchical Reinforcement LearningPoster
Divide and Conquer: Learning Label Distribution with SubtasksPoster
Diving into Self-Evolving Training for Multimodal ReasoningPoster
Do Bayesian Neural Networks Actually Behave Like Bayesian Models?Poster
Do Multiple Instance Learning Models Transfer?Spotlight
Do NOT Think That Much for 2+3=? On the Overthinking of Long Reasoning ModelsPoster
Do Not Mimic My Voice : Speaker Identity Unlearning for Zero-Shot Text-to-SpeechPoster
Do We Really Need Message Passing in Brain Network Modeling?Spotlight
DocKS-RAG: Optimizing Document-Level Relation Extraction through LLM-Enhanced Hybrid Prompt TuningPoster
DocVXQA: Context-Aware Visual Explanations for Document Question AnsweringPoster
Does Data Scaling Lead to Visual Compositional Generalization?Poster
Does Generation Require Memorization? Creative Diffusion Models using Ambient DiffusionPoster
Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?Poster
Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated LearningPoster
Domain-Adapted Diffusion Model for PROTAC Linker Design Through the Lens of Density Ratio in Chemical SpacePoster
Domain2Vec: Vectorizing Datasets to Find the Optimal Data Mixture without TrainingPoster
Don't Restart, Just Reuse: Reoptimizing MILPs with Dynamic ParametersPoster
Double Machine Learning for Causal Inference under Shared-State InterferencePoster
Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer FilteringPoster
Doubly Robust Fusion of Many Treatments for Policy LearningPoster
DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion ModelPoster
DragSolver: A Multi-Scale Transformer for Real-World Automotive Drag Coefficient EstimationPoster
Drug-TTA: Test-Time Adaptation for Drug Virtual Screening via Multi-task Meta-Auxiliary LearningPoster
Dual Feature Reduction for the Sparse-group Lasso and its Adaptive VariantPoster
DyCodeEval: Dynamic Benchmarking of Reasoning Capabilities in Code Large Language Models Under Data ContaminationPoster
DyPolySeg: Taylor Series-Inspired Dynamic Polynomial Fitting Network for Few-shot Point Cloud Semantic SegmentationPoster
DynaMind: Reasoning over Abstract Video Dynamics for Embodied Decision-MakingPoster
Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction TuningPoster
Dynamic Similarity Graph Construction with Kernel Density EstimationPoster
Dynamic Sparse Training of Diagonally Sparse NetworksPoster
Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging DataPoster
Dynamical phases of short-term memory mechanisms in RNNsPoster
E-LDA: Toward Interpretable LDA Topic Models with Strong Guarantees in Logarithmic Parallel TimePoster
EAGLES: Towards Effective, Efficient, and Economical Federated Graph Learning via Unified SparsificationPoster
EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian OptimizationPoster
EEG-Language Pretraining for Highly Label-Efficient Clinical PhenotypingPoster
EFDTR: Learnable Elliptical Fourier Descriptor Transformer for Instance SegmentationPoster
EGPlace: An Efficient Macro Placement Method via Evolutionary Search with Greedy Repositioning Guided MutationPoster
ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in RoboticsPoster
ELITE: Enhanced Language-Image Toxicity Evaluation for SafetyPoster
ELMO : Efficiency via Low-precision and Peak Memory Optimization in Large Output SpacesPoster
ELoRA: Low-Rank Adaptation for Equivariant GNNsPoster
ENAHPool: The Edge-Node Attention-based Hierarchical Pooling for Graph Neural NetworksPoster
ENSUR: Equitable and Statistically Unbiased RecommendationPoster
EPIC: Efficient Position-Independent Caching for Serving Large Language ModelsPoster
ERICT: Enhancing Robustness by Identifying Concept Tokens in Zero-Shot Vision Language ModelsPoster
ETTA: Elucidating the Design Space of Text-to-Audio ModelsPoster
Earley-Driven Dynamic Pruning for Efficient Structured DecodingPoster
EcoMapper: Generative Modeling for Climate-Aware Satellite ImageryPoster
EditLord: Learning Code Transformation Rules for Code EditingPoster
Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image ManipulationPoster
EduLLM: Leveraging Large Language Models and Framelet-Based Signed Hypergraph Neural Networks for Student Performance PredictionPoster
EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuningPoster
Efficient ANN-SNN Conversion with Error Compensation LearningPoster
Efficient Bisection Projection to Ensure Neural-Network Solution Feasibility for Optimization over General SetPoster
Efficient Core-set Selection for Deep Learning Through Squared Loss MinimizationPoster
Efficient Curvature-Aware Hypergradient Approximation for Bilevel OptimizationPoster
Efficient Diffusion Models for Symmetric ManifoldsPoster
Efficient Federated Incomplete Multi-View ClusteringPoster
Efficient Fine-Grained Guidance for Diffusion Model Based Symbolic Music GenerationPoster
Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference GuidanceSpotlight
Efficient Generative Modeling with Residual Vector Quantization-Based TokensPoster
Efficient Graph Continual Learning via Lightweight Graph Neural Tangent Kernels-based Dataset DistillationPoster
Efficient Heterogeneity-Aware Federated Active Data SelectionPoster
Efficient Length-Generalizable Attention via Causal Retrieval for Long-Context Language ModelingPoster
Efficient LiDAR Reflectance Compression via Scanning SerializationPoster
Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep DeploymentPoster
Efficient Long Context Fine-tuning with Chunk FlowPoster
Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and ReflowPoster
Efficient Motion Prompt Learning for Robust Visual TrackingPoster
Efficient Multi-modal Long Context Learning for Training-free AdaptationPoster
Efficient Multivariate Robust Mean Estimation Under Mean-Shift ContaminationPoster
Efficient Network Automatic Relevance DeterminationPoster
Efficient Noise Calculation in Deep Learning-based MRI ReconstructionsPoster
Efficient Online Reinforcement Learning for Diffusion PolicyPoster
Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold MethodPoster
Efficient Parallel Training Methods for Spiking Neural Networks with Constant Time ComplexityPoster
Efficient Personalized Adaptation for Physiological Signal Foundation ModelPoster
Efficient Quantification of Multimodal Interaction at Sample LevelPoster
Efficient Robotic Policy Learning via Latent Space Backward PlanningPoster
Efficient Robust Conformal Prediction via Lipschitz-Bounded NetworksPoster
Efficient Skill Discovery via Regret-Aware OptimizationPoster
Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask OptimizationSpotlight
Efficient and Privacy-Preserving Soft Prompt Transfer for LLMsPoster
Efficient and Separate Authentication Image Steganography NetworkSpotlight
Efficiently Access Diffusion Fisher: Within the Outer Product Span SpacePoster
Efficiently Vectorized MCMC on Modern AcceleratorsSpotlight
EgoPrivacy: What Your First-Person Camera Says About You?Poster
Ehrenfeucht-Haussler Rank and Chain of ThoughtPoster
Eigen Analysis of Conjugate Kernel and Neural Tangent KernelPoster
Eigenspectrum Analysis of Neural Networks without Aspect Ratio BiasPoster
Elucidating Flow Matching ODE Dynamics via Data Geometry and DenoisersPoster
Elucidating the Design Space of Multimodal Protein Language ModelsSpotlight
Embedding Safety into RL: A New Take on Trust Region MethodsPoster
Emergence and Effectiveness of Task Vectors in In-Context Learning: An Encoder Decoder PerspectiveSpotlight
Emergent Response Planning in LLMsPoster
EmoGrowth: Incremental Multi-label Emotion Decoding with Augmented Emotional Relation GraphPoster
Emoji Attack: Enhancing Jailbreak Attacks Against Judge LLM DetectionPoster
Empirical Privacy VariancePoster
Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow NetworksPoster
Empowering World Models with Reflection for Embodied Video PredictionPoster
EnIGMA: Interactive Tools Substantially Assist LM Agents in Finding Security VulnerabilitiesPoster
Enabling Optimal Decisions in Rehearsal Learning under CARE ConditionPoster
EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic EncryptionPoster
End-to-End Learning Framework for Solving Non-Markovian Optimal ControlPoster
Energy-Based Flow Matching for Generating 3D Molecular StructurePoster
Enforcing Idempotency in Neural NetworksPoster
Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold InterpolationSpotlight
Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model ReliabilityPoster
Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing LossSpotlight
Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial ExplorationPoster
Enhancing Decision-Making of Large Language Models via Actor-CriticPoster
Enhancing Diversity In Parallel Agents: A Maximum State Entropy Exploration StoryPoster
Enhancing Foundation Models with Federated Domain Knowledge InfusionPoster
Enhancing Graph Contrastive Learning for Protein Graphs from Perspective of InvariancePoster
Enhancing Graph Invariant Learning from a Negative Inference PerspectivePoster
Enhancing Ligand Validity and Affinity in Structure-Based Drug Design with Multi-Reward OptimizationPoster
Enhancing Logits Distillation with Plug&Play Kendall's $\tau$ Ranking LossPoster
Enhancing Parallelism in Decentralized Stochastic Convex OptimizationPoster
Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language ModelsPoster
Enhancing Spectral GNNs: From Topology and Perturbation PerspectivesPoster
Enhancing Target-unspecific Tasks through a Features MatrixPoster
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering PerspectivePoster
Enhancing Visual Localization with Cross-Domain Image GenerationPoster
Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional NetworksPoster
EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in ClassificationPoster
Ensemble Distribution Distillation via Flow MatchingPoster
Ensemble Learned Bloom Filters: Two Oracles are Better than OnePoster
Epsilon-VAE: Denoising as Visual DecodingPoster
EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization FormulationsPoster
Equivalence is All: A Unified View for Self-supervised Graph LearningOral
Equivariant Neural Tangent KernelsPoster
Equivariant Polynomial Functional NetworksPoster
Ergodic Generative FlowsPoster
Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical SystemsPoster
EvFocus: Learning to Reconstruct Sharp Images from Out-of-Focus Event StreamsPoster
Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem SolvingPoster
Evaluating Neuron Explanations: A Unified Framework with Sanity ChecksPoster
EvoControl: Multi-Frequency Bi-Level Control for High-Frequency Continuous ControlPoster
EvoMesh: Adaptive Physical Simulation with Hierarchical Graph EvolutionsPoster
EvoPress: Accurate Dynamic Model Compression via Evolutionary SearchPoster
Evolving Minds: Logic-Informed Inference from Temporal Action PatternsPoster
Evolving Prompts In-Context: An Open-ended, Self-replicating PerspectivePoster
Ex-VAD: Explainable Fine-grained Video Anomaly Detection Based on Visual-Language ModelsPoster
ExLM: Rethinking the Impact of $\texttt{[MASK]}$ Tokens in Masked Language ModelsPoster
Exact Recovery of Sparse Binary Vectors from Generalized Linear MeasurementsPoster
Exact Upper and Lower Bounds for the Output Distribution of Neural Networks with Random InputsPoster
Exactly Tight Information-theoretic Generalization Bounds via Binary Jensen-Shannon DivergencePoster
Exogenous Isomorphism for Counterfactual IdentifiabilitySpotlight
ExpProof : Operationalizing Explanations for Confidential Models with ZKPsPoster
Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of ExpertsPoster
Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal RepresentationsPoster
Explaining the role of Intrinsic Dimensionality in Adversarial TrainingPoster
Explaining, Fast and Slow: Abstraction and Refinement of Provable ExplanationsPoster
Explicit Discovery of Nonlinear Symmetries from Dynamic DataPoster
Explicit Exploration for High-Welfare Equilibria in Game-Theoretic Multiagent Reinforcement LearningPoster
Explicit Preference Optimization: No Need for an Implicit Reward ModelPoster
Exploiting Curvature in Online Convex Optimization with Delayed FeedbackPoster
Exploiting Presentative Feature Distributions for Parameter-Efficient Continual Learning of Large Language ModelsPoster
Exploiting Similarity for Computation and Communication-Efficient Decentralized OptimizationPoster
Exploring Criteria of Loss Reweighting to Enhance LLM UnlearningPoster
Exploring Invariance in Images through One-way Wave EquationsPoster
Exploring Large Action Sets with Hyperspherical Embeddings using von Mises-Fisher SamplingPoster
Exploring Vision Semantic Prompt for Efficient Point Cloud UnderstandingPoster
Exponential Family Variational Flow Matching for Tabular Data GenerationPoster
Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving RegularizationPoster
ExtPose: Robust and Coherent Pose Estimation by Extending ViTsPoster
Extracting Rare Dependence Patterns via Adaptive Sample ReweightingPoster
Extreme Value Policy Optimization for Safe Reinforcement LearningPoster
FAB-PPI: Frequentist, Assisted by Bayes, Prediction-Powered InferencePoster
FDGen: A Fairness-Aware Graph Generation ModelPoster
FEAT-KD: Learning Concise Representations for Single and Multi-Target Regression via TabNet Knowledge DistillationPoster
FG-CLIP: Fine-Grained Visual and Textual AlignmentPoster
FIC-TSC: Learning Time Series Classification with Fisher Information ConstraintPoster
FLAM: Frame-Wise Language-Audio ModelingPoster
FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language ModelsPoster
FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision MakingPoster
FRUGAL: Memory-Efficient Optimization by Reducing State Overhead for Scalable TrainingPoster
FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient EstimationPoster
FSTLLM: Spatio-Temporal LLM for Few Shot Time Series ForecastingPoster
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free GuaranteesPoster
Fair Clustering via AlignmentPoster
FairICP: Encouraging Equalized Odds via Inverse Conditional PermutationPoster
FairPFN: A Tabular Foundation Model for Causal FairnessPoster
Fairness Overfitting in Machine Learning: An Information-Theoretic PerspectivePoster
Fairness on Principal Stratum: A New Perspective on Counterfactual FairnessPoster
Falcon: Fast Visuomotor Policies via Partial DenoisingPoster
False Coverage Proportion Control for Conformal PredictionPoster
Fast Estimation of Partial Dependence Functions using TreesPoster
Fast Exact Unlearning for In-Context Learning Data for LLMsPoster
Fast Incomplete Multi-view Clustering by Flexible Anchor LearningPoster
Fast Inference with Kronecker-Sparse MatricesPoster
Fast Large Language Model Collaborative Decoding via SpeculationPoster
Fast Min-$\epsilon$ Segmented Regression using Constant-Time Segment MergingPoster
Fast Tensor Completion via Approximate Richardson IterationPoster
Fast and Low-Cost Genomic Foundation Models via Outlier RemovalPoster
Fast and Provable Algorithms for Sparse PCA with Improved Sample ComplexityPoster
Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized EnvironmentsPoster
Fast, Accurate Manifold Denoising by Tunneling Riemannian OptimizationPoster
FastCAV: Efficient Computation of Concept Activation Vectors for Explaining Deep Neural NetworksPoster
Faster Approximation Algorithms for k-Center via Data ReductionPoster
Faster Rates for Private Adversarial BanditsPoster
Faster Stochastic Optimization with Arbitrary Delays via Adaptive Asynchronous Mini-BatchingPoster
Faster and Stronger: When ANN-SNN Conversion Meets Parallel Spiking CalculationPoster
Feasible Action Search for Bandit Linear Programs via Thompson SamplingPoster
FeatSharp: Your Vision Model Features, SharperPoster
Feature Importance Metrics in the Presence of Missing DataPoster
Feature Learning beyond the Lazy-Rich Dichotomy: Insights from Representational GeometrySpotlight
Feature Shift Localization NetworkPoster
Feature learning from non-Gaussian inputs: the case of Independent Component Analysis in high dimensionsSpotlight
Feature out! Let Raw Image as Your Condition for Blind Face RestorationPoster
Feature-Mapping Topology Optimization with Neural Heaviside Signed Distance FunctionsPoster
FedBEns: One-Shot Federated Learning based on Bayesian EnsemblePoster
FedClean: A General Robust Label Noise Correction for Federated LearningPoster
FedECADO: A Dynamical System Model of Federated LearningPoster
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt LearningPoster
FedPHA: Federated Prompt Learning for Heterogeneous Client AdaptationPoster
FedSMU: Communication-Efficient and Generalization-Enhanced Federated Learning through Symbolic Model UpdatesPoster
FedSSI: Rehearsal-Free Continual Federated Learning with Synergistic Synaptic IntelligenceSpotlight
Federated Causal Structure Learning with Non-identical Variable SetsPoster
Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic AdaptationPoster
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning FrameworkSpotlight
Federated In-Context Learning: Iterative Refinement for Improved Answer QualityPoster
Federated Incomplete Multi-view Clustering with Globally Fused Graph GuidancePoster
Federated Learning for Feature Generalization with Convex ConstraintsPoster
Federated Node-Level Clustering Network with Cross-Subgraph Link MendingPoster
Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning FrameworkPoster
Feedforward Few-shot Species Range EstimationPoster
Few-Shot Learner Generalizes Across AI-Generated Image DetectionPoster
FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional NetworksPoster
Field Matching: an Electrostatic Paradigm to Generate and Transfer DataPoster
Finding Wasserstein Ball Center: Efficient Algorithm and The Applications in FairnessPoster
Fine-Grained Captioning of Long Videos through Scene Graph ConsolidationPoster
Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean Field GamesPoster
Finite-Time Analysis of Discrete-Time Stochastic InterpolantsPoster
Finite-Time Convergence Rates in Stochastic Stackelberg Games with Smooth Algorithmic AgentsPoster
Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement LearningPoster
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information GainPoster
Fishers for Free? Approximating the Fisher Information Matrix by Recycling the Squared Gradient AccumulatorSpotlight
Fixed-Confidence Multiple Change Point Identification under Bandit FeedbackPoster
Fixing the Loose Brake: Exponential-Tailed Stopping Time in Best Arm IdentificationPoster
FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic PotentialsSpotlight
Flat-LoRA: Low-Rank Adaptation over a Flat Loss LandscapePoster
Fleet of Agents: Coordinated Problem Solving with Large Language ModelsPoster
Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View CurationPoster
FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image GenerationPoster
FlexiClip: Locality-Preserving Free-Form Character AnimationPoster
FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-IdentificationPoster
Flexibility-conditioned protein structure design with flow matchingPoster
Flexible, Efficient, and Stable Adversarial Attacks on Machine UnlearningPoster
FloE: On-the-Fly MoE Inference on Memory-constrained GPUPoster
Floating-Point Neural Networks Can Represent Almost All Floating-Point FunctionsPoster
Flopping for FLOPs: Leveraging Equivariance for Computational EfficiencySpotlight
Flow Matching for Denoised Social RecommendationPoster
Flow Matching for Few-Trial Neural Adaptation with Stable Latent DynamicsPoster
Flow-based Domain Randomization for Learning and Sequencing Robotic SkillsPoster
FlowDrag: 3D-aware Drag-based Image Editing with Mesh-guided Deformation Vector Flow FieldsSpotlight
Flowing Datasets with Wasserstein over Wasserstein Gradient FlowsOral
Fluctuations of the largest eigenvalues of transformed spiked Wigner matricesPoster
Focal-SAM: Focal Sharpness-Aware Minimization for Long-Tailed ClassificationPoster
Focus On This, Not That! Steering LLMs with Adaptive Feature SpecificationPoster
Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset SelectionOral
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph LanguagesPoster
Fragments to Facts: Partial-Information Fragment Inference from LLMsPoster
Fraud-Proof Revenue Division on Subscription PlatformsPoster
FreeMesh: Boosting Mesh Generation with Coordinates MergingPoster
From Black Boxes to Transparent Minds: Evaluating and Enhancing the Theory of Mind in Multimodal Large Language ModelsPoster
From Complex to Atomic: Enhancing Augmented Generation via Knowledge-Aware Dual Rewriting and ReasoningPoster
From Crowdsourced Data to High-quality Benchmarks: Arena-Hard and Benchbuilder PipelinePoster
From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash EquilibriumPoster
From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction ModelsPoster
From Jack of All Trades to Master of One: Specializing LLM-based Autoraters to a Test SetPoster
From Local Details to Global Context: Advancing Vision-Language Models with Attention-Based SelectionPoster
From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and ApplicationsPoster
From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information?Poster
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature SelectionPoster
From Spectrum-free towards Baseline-view-free: Double-track Proximity Driven Multi-view ClusteringPoster
From Theory to Practice: Rethinking Green and Martin Kernels for Unleashing Graph TransformersPoster
From Thousands to Billions: 3D Visual Language Grounding via Render-Supervised Distillation from 2D VLMsPoster
From Token to Rhythm: A Multi-Scale Approach for ECG-Language PretrainingPoster
From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE ControlPoster
From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel ControlOral
Fully Dynamic Embedding into $\ell_p$ SpacesPoster
Fully Dynamic Euclidean Bi-Chromatic Matching in Sublinear Update TimeOral
Function Encoders: A Principled Approach to Transfer Learning in Hilbert SpacesPoster
Function-to-Style Guidance of LLMs for Code TranslationPoster
Functional Alignment Can Mislead: Examining Model StitchingSpotlight
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled NewtonOral
Fundamental Limits of Visual Autoregressive Transformers: Universal Approximation AbilitiesPoster
Fundamental limits of learning in sequence multi-index models and deep attention networks: high-dimensional asymptotics and sharp thresholdsPoster
FuseUNet: A Multi-Scale Feature Fusion Method for U-like NetworksPoster
Fusing Reward and Dueling Feedback in Stochastic BanditsPoster
G-Sim: Generative Simulations with Large Language Models and Gradient-Free CalibrationPoster
GANQ: GPU-Adaptive Non-Uniform Quantization for Large Language ModelsPoster
GAPrompt: Geometry-Aware Point Cloud Prompt for 3D Vision ModelPoster
GCAL: Adapting Graph Models to Evolving Domain ShiftsPoster
GEFA: A General Feature Attribution Framework Using Proxy Gradient EstimationPoster
GHOST: Generalizable One-Shot Federated Graph Learning with Proxy-Based Topology Knowledge RetentionPoster
GIVE: Structured Reasoning of Large Language Models with Knowledge Graph Inspired Veracity ExtrapolationPoster
GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace RegressionSpotlight
GLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric AlgebrasPoster
GMAIL: Generative Modality Alignment for generated Image LearningSpotlight
GPEN: Global Position Encoding Network for Enhanced Subgraph Representation LearningPoster
GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric CalibrationPoster
GRADEO: Towards Human-Like Evaluation for Text-to-Video Generation via Multi-Step ReasoningPoster
GRAIL: Graph Edit Distance and Node Alignment using LLM-Generated CodePoster
GRAM: A Generative Foundation Reward Model for Reward GeneralizationPoster
GRU: Mitigating the Trade-off between Unlearning and Retention for LLMsPoster
GS-Bias: Global-Spatial Bias Learner for Single-Image Test-Time Adaptation of Vision-Language ModelsPoster
GSM-$\infty$: How Do your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length?Poster
GTR: A General, Multi-View, and Dynamic Framework for Trajectory Representation LearningPoster
Galileo: Learning Global & Local Features of Many Remote Sensing ModalitiesPoster
Gamma Distribution PCA-Enhanced Feature Learning for Angle-Robust SAR Target RecognitionPoster
Gandalf the Red: Adaptive Security for LLMsPoster
GaussMark: A Practical Approach for Structural Watermarking of Language ModelsPoster
GaussMarker: Robust Dual-Domain Watermark for Diffusion ModelsPoster
Gaussian Mixture Flow Matching ModelsPoster
GenZSL: Generative Zero-Shot Learning Via Inductive Variational AutoencoderPoster
General agents need world modelsPoster
Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization TasksPoster
Generalizable Multi-Camera 3D Object Detection from a Single Source via Fourier Cross-View LearningPoster
Generalization Analysis for Controllable LearningPoster
Generalization Analysis for Supervised Contrastive Representation Learning under Non-IID SettingsPoster
Generalization Bounds via Meta-Learned Model Representations: PAC-Bayes and Sample Compression HypernetworksPoster
Generalization Performance of Ensemble Clustering: From Theory to AlgorithmPoster
Generalization Principles for Inference over Text-Attributed Graphs with Large Language ModelsPoster
Generalization and Robustness of the Tilted Empirical RiskPoster
Generalization in Federated Learning: A Conditional Mutual Information FrameworkPoster
Generalization of noisy SGD in unbounded non-convex settingsPoster
Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution RegularizationPoster
Generalized Interpolating Discrete DiffusionPoster
Generalized Random Forests Using Fixed-Point TreesSpotlight
Generalized Smooth Bilevel Optimization with Nonconvex Lower-LevelPoster
Generalized Venn and Venn-Abers Calibration with Applications in Conformal PredictionPoster
Generalized additive models via direct optimization of regularized decision stump forestsPoster
Generalizing Causal Effects from Randomized Controlled Trials to Target Populations across Diverse EnvironmentsPoster
Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time SeriesPoster
Generation from Noisy ExamplesPoster
Generative Audio Language Modeling with Continuous-valued Tokens and Masked Next-Token PredictionPoster
Generative Data Mining with Longtail-Guided DiffusionPoster
Generative Human Trajectory Recovery via Embedding-Space Conditional DiffusionPoster
Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency LearningPoster
Generative Point Cloud RegistrationPoster
Generative Social Choice: The Next GenerationOral
Geometric Algebra Planes: Convex Implicit Neural VolumesPoster
Geometric Contact Flows: Contactomorphisms for Dynamics and ControlPoster
Geometric Feature Embedding for Effective 3D Few-Shot Class Incremental LearningPoster
Geometric Generative Modeling with Noise-Conditioned Graph NetworksPoster
Geometric Hyena Networks for Large-scale Equivariant LearningSpotlight
Geometric Median (GM) Matching for Robust k-Subset Selection from Noisy DataPoster
Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit ProblemsPoster
Geometric and Physical Constraints Synergistically Enhance Neural PDE SurrogatesPoster
Geometry Informed Tokenization of Molecules for Language Model GenerationPoster
Global Context-aware Representation Learning for Spatially Resolved TranscriptomicsPoster
Global Convergence and Rich Feature Learning in $L$-Layer Infinite-Width Neural Networks under $\mu$ ParametrizationPoster
Global Optimization with a Power-Transformed Objective and Gaussian SmoothingPoster
Global curvature for second-order optimization of neural networksPoster
Global-Local Dirichlet Processes for Clustering Grouped Data in the Presence of Group-Specific Idiosyncratic VariablesPoster
GoIRL: Graph-Oriented Inverse Reinforcement Learning for Multimodal Trajectory PredictionPoster
Goal-Oriented Skill Abstraction for Offline Multi-Task Reinforcement LearningPoster
Going Deeper into Locally Differentially Private Graph Neural NetworksOral
GradPS: Resolving Futile Neurons in Parameter Sharing Network for Multi-Agent Reinforcement LearningPoster
Gradient Aligned Regression via Pairwise LossesPoster
Gradient Descent Converges Arbitrarily Fast for Logistic Regression via Large and Adaptive StepsizesPoster
Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMsPoster
Gradient Inversion of Multimodal ModelsPoster
Gradient-based Explanations for Deep Learning Survival ModelsPoster
Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement LearningPoster
Grammar-Forced Translation of Natural Language to Temporal Logic using LLMsPoster
Graph Adaptive Autoregressive Moving Average ModelsSpotlight
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block ModelsPoster
Graph Diffusion for Robust Multi-Agent CoordinationSpotlight
Graph Inverse Style Transfer for Counterfactual ExplainabilityPoster
Graph Minimum Factor Distance and Its Application to Large-Scale Graph Data ClusteringPoster
Graph Neural Network Generalization With Gaussian Mixture Model Based AugmentationPoster
Graph World ModelPoster
Graph-Assisted Stitching for Offline Hierarchical Reinforcement LearningPoster
Graph-Based Algorithms for Diverse Similarity SearchPoster
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial OptimizationPoster
Graph4MM: Weaving Multimodal Learning with Structural InformationPoster
GraphCL: Graph-based Clustering for Semi-Supervised Medical Image SegmentationPoster
GraphGPT: Generative Pre-trained Graph Eulerian TransformerPoster
Great Models Think Alike and this Undermines AI OversightSpotlight
Gridded Transformer Neural Processes for Spatio-Temporal DataSpotlight
Griffin: Towards a Graph-Centric Relational Database Foundation ModelPoster
GrokFormer: Graph Fourier Kolmogorov-Arnold TransformersPoster
Grokking Beyond the Euclidean Norm of Model ParametersPoster
Grokking at the Edge of Linear SeparabilityPoster
Grokking in the Wild: Data Augmentation for Real-World Multi-Hop Reasoning with TransformersPoster
GuardAgent: Safeguard LLM Agents via Knowledge-Enabled ReasoningPoster
Guided Search Strategies in Non-Serializable Environments with Applications to Software Engineering AgentsPoster
Guided Structural Inference: Leveraging Priors with Soft Gating MechanismsPoster
Guided Zeroth-Order Methods for Stochastic Non-convex Problems with Decision-Dependent DistributionsPoster
GuidedQuant: Large Language Model Quantization via Exploiting End Loss GuidancePoster
Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative DecodingPoster
H-Tuning: Toward Low-Cost and Efficient ECG-based Cardiovascular Disease Detection with Pre-Trained ModelsPoster
HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model TrainingPoster
HEAP: Hyper Extended A-PDHG Operator for Constrained High-dim PDEsPoster
HGOT: Self-supervised Heterogeneous Graph Neural Network with Optimal TransportPoster
HPS: Hard Preference Sampling for Human Preference AlignmentPoster
HYGMA: Hypergraph Coordination Networks with Dynamic Grouping for Multi-Agent Reinforcement LearningPoster
Habitizing Diffusion Planning for Efficient and Effective Decision MakingPoster
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated MarginPoster
HaploVL: A Single-Transformer Baseline for Multi-Modal UnderstandingPoster
Hardware and Software Platform InferencePoster
HarmoniCa: Harmonizing Training and Inference for Better Feature Caching in Diffusion Transformer AccelerationPoster
Harmonizing Geometry and Uncertainty: Diffusion with HyperspheresPoster
Harnessing Heterogeneous Statistical Strength for Personalized Federated Learning via Hierarchical Bayesian InferencePoster
Heads up! Large Language Models Can Perform Tasks Without Your Instruction via Selective Attention Head MaskingPoster
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass UpdatePoster
Hessian Geometry of Latent Space in Generative ModelsPoster
HetSSNet: Spatial-Spectral Heterogeneous Graph Learning Network for Panchromatic and Multispectral Images FusionPoster
Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data SourcesPoster
Heterogeneous Label Shift: Theory and AlgorithmPoster
Heterogeneous Sufficient Dimension Reduction and Subspace ClusteringPoster
Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed TreesPoster
Hgformer: Hyperbolic Graph Transformer for Collaborative FilteringPoster
Hi-Patch: Hierarchical Patch GNN for Irregular Multivariate Time SeriesPoster
HiRemate: Hierarchical Approach for Efficient Re-materialization of Neural NetworksPoster
Hidden No More: Attacking and Defending Private Third-Party LLM InferencePoster
Hide & Seek: Transformer Symmetries Obscure Sharpness & Riemannian Geometry Finds ItSpotlight
Hierarchical Graph Tokenization for Molecule-Language AlignmentPoster
Hierarchical Masked Autoregressive Models with Low-Resolution Token PivotsPoster
Hierarchical Overlapping Clustering on Graphs: Cost Function, Algorithm and ScalabilityPoster
Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic VerificationPoster
Hierarchical Refinement: Optimal Transport to Infinity and BeyondOral
Hierarchical Reinforcement Learning with Targeted Causal InterventionsPoster
Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional SubgoalsPoster
High Dynamic Range Novel View Synthesis with Single ExposurePoster
High Probability Bound for Cross-Learning Contextual Bandits with Unknown Context DistributionsPoster
High-Dimensional Tensor Regression With Oracle PropertiesPoster
Highly Compressed Tokenizer Can Generate Without TrainingPoster
Holistic Physics Solver: Learning PDEs in a Unified Spectral-Physical SpacePoster
Homophily Enhanced Graph Domain AdaptationPoster
How Compositional Generalization and Creativity Improve as Diffusion Models are TrainedPoster
How Contaminated Is Your Benchmark? Measuring Dataset Leakage in Large Language Models with Kernel DivergencePoster
How Distributed Collaboration Influences the Diffusion Model Training? A Theoretical PerspectivePoster
How Do Images Align and Complement LiDAR? Towards a Harmonized Multi-modal 3D Panoptic SegmentationPoster
How Do Large Language Monkeys Get Their Power (Laws)?Oral
How Do Transformers Learn Variable Binding in Symbolic Programs?Poster
How Effective Can Dropout Be in Multiple Instance Learning ?Poster
How Expressive are Knowledge Graph Foundation Models?Poster
How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization GuaranteesPoster
How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit BiasPoster
How Transformers Learn Structured Data: Insights From Hierarchical FilteringPoster
How does Labeling Error Impact Contrastive Learning? A Perspective from Data Dimensionality ReductionPoster
How to Evaluate and Mitigate IP Infringement in Visual Generative AI?Poster
How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary ObjectsPoster
How to Train Your Multi-Exit Model? Analyzing the Impact of Training StrategiesPoster
Human Body Restoration with One-Step Diffusion Model and A New BenchmarkPoster
Human Cognition-Inspired Hierarchical Fuzzy Learning MachinePoster
Human-Aligned Image Models Improve Visual Decoding from the BrainPoster
Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated LearningPoster
Hybrid Quantum-Classical Multi-Agent PathfindingPoster
Hybrid Spiking Vision Transformer for Object Detection with Event CamerasPoster
HybridGS: High-Efficiency Gaussian Splatting Data Compression using Dual-Channel Sparse Representation and Point Cloud EncoderPoster
Hyper-Transforming Latent Diffusion ModelsPoster
HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series ForecastingPoster
HyperIV: Real-time Implied Volatility SmoothingPoster
HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural NetworksPoster
HyperTree Planning: Enhancing LLM Reasoning via Hierarchical ThinkingPoster
Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential EquationsPoster
Hyperspherical Normalization for Scalable Deep Reinforcement LearningSpotlight
Hypo3D: Exploring Hypothetical Reasoning in 3DPoster
Hypothesis Testing for Generalized Thurstone ModelsPoster
I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion ModelsPoster
IBCircuit: Towards Holistic Circuit Discovery with Information BottleneckPoster
ICLShield: Exploring and Mitigating In-Context Learning Backdoor AttacksPoster
IL-SOAR : Imitation Learning with Soft Optimistic Actor cRiticPoster
IMPACT: Iterative Mask-based Parallel Decoding for Text-to-Audio Generation with Diffusion ModelingPoster
IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series PredictionPoster
INRFlow: Flow Matching for INRs in Ambient SpacePoster
IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion ModelsPoster
IT$^3$: Idempotent Test-Time TrainingPoster
ITBench: Evaluating AI Agents across Diverse Real-World IT Automation TasksOral
ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask DatasetPoster
Identifiable Object Representations under Spatial AmbiguitiesPoster
Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear ObservationsPoster
Identifying Causal Direction via Variational Bayesian CompressionSpotlight
Identifying Metric Structures of Deep Latent Variable ModelsPoster
Identifying Neural Dynamics Using Interventional State Space ModelsPoster
Identifying and Understanding Cross-Class Features in Adversarial TrainingPoster
Identifying biological perturbation targets through causal differential networksPoster
Imitation Learning from a Single Temporally Misaligned VideoPoster
Implicit Bias of Gradient Descent for Non-Homogeneous Deep NetworksPoster
Implicit Regularization for Tubal Tensor Factorizations via Gradient DescentOral
Implicit Riemannian Optimism with Applications to Min-Max ProblemsPoster
Implicit Subgraph Neural NetworkPoster
Importance Sampling for Nonlinear ModelsPoster
Improved Algorithm for Deep Active Learning under Imbalance via Optimal SeparationPoster
Improved Approximations for Hard Graph Problems using PredictionsPoster
Improved Coresets for Vertical Federated Learning: Regularized Linear and Logistic RegressionsPoster
Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization SchemePoster
Improved Expressivity of Hypergraph Neural Networks through High-Dimensional Generalized Weisfeiler-Leman AlgorithmsPoster
Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex OptimizationPoster
Improved Learning via k-DTW: A Novel Dissimilarity Measure for CurvesPoster
Improved Lower Bounds for First-order Stochastic Non-convex Optimization under Markov SamplingPoster
Improved Theoretically-Grounded Evolutionary Algorithms for Subset Selection with a Linear Cost ConstraintPoster
Improved and Oracle-Efficient Online $\ell_1$-MulticalibrationPoster
Improving Compositional Generation with Diffusion Models Using Lift ScoresPoster
Improving Consistency Models with Generator-Augmented FlowsSpotlight
Improving Continual Learning Performance and Efficiency with Auxiliary ClassifiersPoster
Improving Diversity in Language Models: When Temperature Fails, Change the LossPoster
Improving Flow Matching by Aligning Flow DivergencePoster
Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight AveragingPoster
Improving Generalization with Flat Hilbert Bayesian InferencePoster
Improving Memory Efficiency for Training KANs via Meta LearningPoster
Improving Model Alignment Through Collective Intelligence of Open-Source ModelsPoster
Improving Multi-Class Calibration through Normalization-Aware Isotonic TechniquesPoster
Improving Multimodal Learning Balance and Sufficiency through Data RemixingPoster
Improving Out-of-Distribution Detection via Dynamic Covariance CalibrationPoster
Improving Out-of-Distribution Detection with Markov Logic NetworksPoster
Improving Parallel Program Performance with LLM Optimizers via Agent-System InterfacesPoster
Improving Rationality in the Reasoning Process of Language Models through Self-playing GamePoster
Improving Reward Model Generalization from Adversarial Process Enhanced PreferencesPoster
Improving Soft Unification with Knowledge Graph Embedding MethodsPoster
Improving Transformer World Models for Data-Efficient RLPoster
Improving Value Estimation Critically Enhances Vanilla Policy GradientPoster
Improving Zero-Shot Adversarial Robustness in Vision-Language Models by Closed-form Alignment of Adversarial Path SimplicesSpotlight
Improving the Continuity of Goal-Achievement Ability via Policy Self-Regularization for Goal-Conditioned Reinforcement LearningPoster
Improving the Diffusability of AutoencodersPoster
Improving the Effective Receptive Field of Message-Passing Neural NetworksPoster
Improving the Scaling Laws of Synthetic Data with Deliberate PracticeOral
Improving the Statistical Efficiency of Cross-Conformal PredictionPoster
Improving the Variance of Differentially Private Randomized Experiments through ClusteringPoster
In-Context Adaptation to Concept Drift for Learned Database OperationsPoster
In-Context Deep Learning via Transformer ModelsPoster
In-Context Denoising with One-Layer Transformers: Connections between Attention and Associative Memory RetrievalOral
In-Context Fine-Tuning for Time-Series Foundation ModelsPoster
In-Context Learning as Conditioned Associative Memory RetrievalPoster
In-Context Linear Regression Demystified: Training Dynamics and Mechanistic Interpretability of Multi-Head Softmax AttentionPoster
In-Context Reinforcement Learning From Suboptimal Historical DataPoster
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov GamesPoster
Incorporating Arbitrary Matrix Group Equivariance into KANsPoster
Incremental Gradient Descent with Small Epoch Counts is Surprisingly Slow on Ill-Conditioned ProblemsPoster
Independence Tests for Language ModelsSpotlight
Inducing, Detecting and Characterising Neural Modules: A Pipeline for Functional Interpretability in Reinforcement LearningPoster
Inductive Gradient Adjustment for Spectral Bias in Implicit Neural RepresentationsPoster
Inductive Moment MatchingOral
Inference-Time Alignment of Diffusion Models with Direct Noise OptimizationPoster
Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language ModelsPoster
Info-Coevolution: An Efficient Framework for Data Model CoevolutionPoster
InfoCons: Identifying Interpretable Critical Concepts in Point Clouds via Information TheoryPoster
InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic PerspectiveSpotlight
InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network InferencePoster
Information Bottleneck-guided MLPs for Robust Spatial-temporal ForecastingPoster
Instance Correlation Graph-based Naive BayesSpotlight
Instance-Optimal Pure Exploration for Linear Bandits on Continuous ArmsPoster
Instruct2See: Learning to Remove Any Obstructions Across DistributionsPoster
Instruction-Following Pruning for Large Language ModelsPoster
Integer Programming for Generalized Causal Bootstrap DesignsPoster
Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion ModelsPoster
Integration-free Kernels for Equivariant Gaussian Process ModellingPoster
Interaction-Aware Gaussian Weighting for Clustered Federated LearningPoster
Interchangeable Token Embeddings for Extendable Vocabulary and Alpha-EquivalencePoster
Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution BehaviorsPoster
Interpreting CLIP with Hierarchical Sparse AutoencodersPoster
Interpreting the Repeated Token Phenomenon in Large Language ModelsPoster
Intersectional Fairness in Reinforcement Learning with Large State and Constraint SpacesPoster
Introducing 3D Representation for Dense Volume-to-Volume Translation via Score FusionPoster
Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-TuningPoster
Invariant Deep Uplift Modeling for Incentive Assignment in Online Marketing via Probability of Necessity and SufficiencySpotlight
Inverse Bridge Matching DistillationPoster
Inverse Flow and Consistency ModelsPoster
Inverse Optimization via Learning Feasible RegionsPoster
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal BehaviorsPoster
Inverse problems with experiment-guided AlphaFoldPoster
Investigating Non-Transitivity in LLM-as-a-JudgeSpotlight
Investigating the Overlooked Hessian Structure: From CNNs to LLMsPoster
Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMsPoster
It's My Data Too: Private ML for Datasets with Multi-User Training ExamplesPoster
Iterative Vectors: In-Context Gradient Steering without BackpropagationPoster
Jacobian Sparse Autoencoders: Sparsify Computations, Not Just ActivationsPoster
Janus: Dual-Server Multi-Round Secure Aggregation with Verifiability for Federated LearningPoster
Joint Localization and Activation Editing for Low-Resource Fine-TuningPoster
Joint MoE Scaling Laws: Mixture of Experts Can Be Memory EfficientPoster
Joker: Joint Optimization Framework for Lightweight Kernel MachinesPoster
Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-TuningPoster
K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson ProcessesPoster
KABB: Knowledge-Aware Bayesian Bandits for Dynamic Expert Coordination in Multi-Agent SystemsPoster
KEA: Keeping Exploration Alive by Proactively Coordinating Exploration StrategiesPoster
KGMark: A Diffusion Watermark for Knowledge GraphsPoster
KIND: Knowledge Integration and Diversion for Training Decomposable ModelsPoster
KVTuner: Sensitivity-Aware Layer-Wise Mixed-Precision KV Cache Quantization for Efficient and Nearly Lossless LLM InferencePoster
Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional CoveragePoster
Kernel Quantile Embeddings and Associated Probability MetricsPoster
Kernel-based Unsupervised Embedding Alignment for Enhanced Visual Representation in Vision-language ModelsPoster
KinDEL: DNA-Encoded Library Dataset for Kinase InhibitorsPoster
Knowledge Retention in Continual Model-Based Reinforcement LearningPoster
Knowledge Swapping via Learning and UnlearningPoster
Knowledge-Guided Wasserstein Distributionally Robust OptimizationPoster
KoNODE: Koopman-Driven Neural Ordinary Differential Equations with Evolving Parameters for Time Series AnalysisPoster
Kona: An Efficient Privacy-Preservation Framework for KNN Classification by Communication OptimizationPoster
KoopSTD: Reliable Similarity Analysis between Dynamical Systems via Approximating Koopman Spectrum with Timescale DecouplingPoster
L-Diffusion: Laplace Diffusion for Efficient Pathology Image SegmentationPoster
L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental LearningPoster
LADA: Scalable Label-Specific CLIP Adapter for Continual LearningPoster
LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision ModelsPoster
LAST SToP for Modeling Asynchronous Time SeriesPoster
LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width AllocationPoster
LDMol: A Text-to-Molecule Diffusion Model with Structurally Informative Latent Space Surpasses AR ModelsPoster
LEMoN: Label Error Detection using Multimodal NeighborsPoster
LETS Forecast: Learning Embedology for Time Series ForecastingPoster
LEVIS: Large Exact Verifiable Input Spaces for Neural NetworksPoster
LGDM: Latent Guidance in Diffusion Models for Perceptual EvaluationsPoster
LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-TuningPoster
LIMEFLDL: A Local Interpretable Model-Agnostic Explanations Approach for Label Distribution LearningPoster
LLM Data Selection and Utilization via Dynamic Bi-level OptimizationPoster
LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism IdentificationPoster
LLM-Assisted Semantically Diverse Teammate Generation for Efficient Multi-agent CoordinationPoster
LLM-Augmented Chemical Synthesis and Design Decision ProgramsPoster
LLMScan: Causal Scan for LLM Misbehavior DetectionPoster
LLMs Can Reason Faster Only If We Let ThemPoster
LLMs on the Line: Data Determines Loss-to-Loss Scaling LawsPoster
LLaVA-ReID: Selective Multi-image Questioner for Interactive Person Re-IdentificationPoster
LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3DSpotlight
LRA-QViT: Integrating Low-Rank Approximation and Quantization for Robust and Efficient Vision TransformersPoster
LSCD: Lomb--Scargle Conditioned Diffusion for Time series ImputationPoster
LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language ModelsPoster
La RoSA: Enhancing LLM Efficiency via Layerwise Rotated Sparse ActivationPoster
LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language ModelsPoster
LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology GenerationPoster
Label Distribution Propagation-based Label Completion for CrowdsourcingPoster
Ladder-Residual: Parallelism-Aware Architecture for Accelerating Large Model Inference with Communication OverlappingPoster
LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image SegmentationPoster
LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy OptimizationPoster
Language Models May Verbatim Complete Text They Were Not Explicitly Trained OnSpotlight
Language Models as Implicit Tree SearchPoster
Language Models over Canonical Byte-Pair EncodingsPoster
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k SelectionPoster
Laplace Transform Based Low-Complexity Learning of Continuous Markov SemigroupsPoster
Large Continual Instruction AssistantPoster
Large Displacement Motion Transfer with Unsupervised Anytime InterpolationPoster
Large Language Models are Demonstration Pre-Selectors for ThemselvesPoster
Large Language Models to Diffusion FinetuningPoster
Larger or Smaller Reward Margins to Select Preferences for LLM Alignment?Poster
Latent Action Learning Requires Supervision in the Presence of DistractorsPoster
Latent Imputation before Prediction: A New Computational Paradigm for De Novo Peptide SequencingPoster
Latent Mamba Operator for Partial Differential EquationsPoster
Latent Score-Based Reweighting for Robust Classification on Imbalanced Tabular DataPoster
Latent Thought Models with Variational Bayes Inference-Time ComputationPoster
Latent Variable Causal Discovery under Selection BiasPoster

ICML accepted papers in other years

ICML 2026 (6,634)ICML 2024 (2,610)ICML 2023 (1,828)ICML 2022 (1,228)ICML 2021 (1,181)ICML 2020 (1,082)ICML 2019 (773)ICML 2018 (620)ICML 2017 (433)ICML 2016 (322)ICML 2015 (270)

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