NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models


The Primacy of Magnitude in Low-Rank Adaptation


EngiBench: A Framework for Data-Driven Engineering Design Research


COME: Adding Scene-Centric Forecasting Control to Occupancy World Model


Stochastic Forward-Forward Learning through Representational Dimensionality Compression


Zooming from Context to Cue: Hierarchical Preference Optimization for Multi-Image MLLMs


Struct-Bench: A Benchmark for Differentially Private Structured Text
  Generation


DCI: Dual-Conditional Inversion for Boosting Diffusion-Based Image
  Editing


Robust and Computation-Aware Gaussian Processes


Blending Complementary Memory Systems in Hybrid Quadratic-Linear Transformers


Adjusting Initial Noise to Mitigate Memorization in Text-to-Image Diffusion Models


Wan-Move: Motion-controllable Video Generation via Latent Trajectory Guidance


CAT: Content-Adaptive Image Tokenization


Seg2Any: Open-set Segmentation-Mask-to-Image Generation with Precise
  Shape and Semantic Control


PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models


Hawaii: Hierarchical Visual Knowledge Transfer for Efficient Vision-Language Models


The Price of Sparsity: Sufficient Conditions for Sparse Recovery using Sparse and Sparsified Measurements


Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification


GPO: Learning from Critical Steps to Improve LLM Reasoning


Fair Minimum Labeling: Efficient Temporal Network Activations for Reachability and Equity


Metritocracy: Representative Metrics for Lite Benchmarks


scPilot: Large Language Model Reasoning Toward Automated Single-Cell Analysis and Discovery


Elucidated Rolling Diffusion Models for Probabilistic Weather Forecasting


RSAVQ: Riemannian Sensitivity-Aware Vector Quantization for Large Language Models


A Few Moments Please: Scalable Graphon Learning via Moment Matching


Mitigating Forgetting in LLM Fine-Tuning via Low-Perplexity Token Learning


Conformal Prediction for Causal Effects of Continuous Treatments


Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning


EndoBench: A Comprehensive Evaluation of Multi-Modal Large Language
  Models for Endoscopy Analysis


Data-Dependent Regret Bounds for Constrained MABs


EVOREFUSE: Evolutionary Prompt Optimization for Evaluation and Mitigation of LLM Over-Refusal to Pseudo-Malicious Instructions


Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback


Let LLMs Break Free from Overthinking via Self-Braking Tuning


Spectral Estimation with Free Decompression


DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches


PDEfuncta: Spectrally-Aware Neural Representation for PDE Solution Modeling


Spectral Analysis of Diffusion Models with Application to Schedule Design


Variational Uncertainty Decomposition for In-Context Learning


When Words Outperform Vision: VLMs Can Self-Improve Via Text-Only Training For Human-Centered Decision Making


Future Link Prediction Without Memory or Aggregation


Scaling Offline RL via Efficient and Expressive Shortcut Models


TRACE: Grounding Time Series in Context for Multimodal Embedding and Retrieval


FlexAC: Towards Flexible Control of Associative Reasoning in Multimodal
  Large Language Models


Learning to Specialize: Joint Gating-Expert Training for Adaptive MoEs in Decentralized Settings


Predicting Empirical AI Research Outcomes with Language Models


From Counterfactuals to Trees: Competitive Analysis of Model Extraction Attacks


Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lens


NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation


UltraHR-100K: Enhancing UHR Image Synthesis with A Large-Scale
  High-Quality Dataset


Hierarchical Self-Attention: Generalizing Neural Attention Mechanics to Multi-Scale Problems


SynCL: A Synergistic Training Strategy with Instance-Aware Contrastive Learning for End-to-End Multi-Camera 3D Tracking


Structural Entropy Guided Agent for Detecting and Repairing Knowledge Deficiencies in LLMs


Frame In-N-Out: Unbounded Controllable Image-to-Video Generation


VFRTok: Variable Frame Rates Video Tokenizer with Duration-Proportional
  Information Assumption


Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles


Cost-aware LLM-based Online Dataset Annotation


CausalVerse: Benchmarking Causal Representation Learning with
  Configurable High-Fidelity Simulations


Cooperative Bargaining Games Without Utilities: Mediated Solutions from Direction Oracles


Demystifying Language Model Forgetting with Low-rank Example Associations


PhysVLM-AVR: Active Visual Reasoning for Multimodal Large Language
  Models in Physical Environments


Look Before You Leap: A GUI-Critic-R1 Model for Pre-Operative Error Diagnosis in GUI Automation


MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering


Kuramoto Orientation Diffusion Models


Spectral Compressive Imaging via Chromaticity-Intensity Decomposition


RoMA: Scaling up Mamba-based Foundation Models for Remote Sensing


TRUST: Test-Time Refinement using Uncertainty-Guided SSM Traverses


Jacobian-Based Interpretation of Nonlinear Neural Encoding Model


DexFlyWheel: A Scalable and Self-improving Data Generation Framework for Dexterous Manipulation


VideoRFT: Incentivizing Video Reasoning Capability in MLLMs via
  Reinforced Fine-Tuning


A Generalized Label Shift Perspective for Cross-Domain Gaze Estimation


Open Vision Reasoner: Transferring Linguistic Cognitive Behavior for Visual Reasoning


Partial Information Decomposition via Normalizing Flows in Latent Gaussian Distributions


Lattice Boltzmann Model for Learning Real-World Pixel Dynamicity


IPFormer: Visual 3D Panoptic Scene Completion with Context-Adaptive Instance Proposals


The VLLM Safety Paradox: Dual Ease in Jailbreak Attack and Defense


Incentivizing LLMs to Self-Verify Their Answers


Multivariate Latent Recalibration for Conditional Normalizing Flows


DMWM: Dual-Mind World Model with Long-Term Imagination


Decompile-Bench: Million-Scale Binary-Source Function Pairs for
  Real-World Binary Decompilation


Flash Invariant Point Attention


Subsampled Ensemble Can Improve Generalization Tail Exponentially


STAIR: Addressing Stage Misalignment through Temporal-Aligned Preference Reinforcement Learning


Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning


Towards Unified Multimodal Interleaved Generation via Group Relative Policy Optimization


Hybrid Latent Reasoning via Reinforcement Learning


WISA: World Simulator Assistant for Physics-Aware Text-to-Video Generation


Efficient Large Language Model Inference with Neural Block Linearization


Learning Temporal 3D Semantic Scene Completion via Optical Flow Guidance


Path Gradients after Flow Matching


On the Bias of Next-Token Predictors Toward Systematically Inefficient
  Reasoning: A Shortest-Path Case Study


Can LLMs Reason Over Non-Text Modalities in a Training-Free Manner? A Case Study with In-Context Representation Learning


AutoEdit: Automatic Hyperparameter Tuning for Image Editing


Transductive Conformal Inference for Full Ranking


Sample and Map from a Single Convex Potential: Generation using Conjugate Moment Measures


GeoClip: Geometry-Aware Clipping for Differentially Private SGD


Online Learning of Neural Networks


On Minimax Estimation of Parameters in Softmax-Contaminated Mixture of Experts


Doubly Robust Alignment for Large Language Models


Layer as Puzzle Pieces: Compressing Large Language Models through Layer Concatenation


Split conformal classification with unsupervised calibration


IR3D-Bench: Evaluating Vision-Language Model Scene Understanding as   Agentic Inverse Rendering


ExAct: A Video-Language Benchmark for Expert Action Analysis


Constructing an Optimal Behavior Basis for the Option Keyboard


Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search


XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation


FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning


Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes


Learning-Augmented Online Bipartite Fractional Matching


Representation Entanglement for Generation:Training Diffusion
  Transformers Is Much Easier Than You Think


AudSemThinker: Enhancing Audio-Language Models through Reasoning over
  Semantics of Sound


Incentivizing Time-Aware Fairness in Data Sharing


VORTA: Efficient Video Diffusion via Routing Sparse Attention


A Pre-training Framework for Relational Data with Information-theoretic Principles


GUARDIAN: Safeguarding LLM Multi-Agent Collaborations with Temporal Graph Modeling


FlexVAR: Flexible Visual Autoregressive Modeling without Residual Prediction


RiOSWorld: Benchmarking the Risk of Multimodal Computer-Use Agents


Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning


VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verification


On the Closed-Form of Flow Matching: Generalization Does Not Arise from Target Stochasticity


Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery


Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling


Better Language Model Inversion by Compactly Representing Next-Token   Distributions


Flexible inference of learning rules from de novo learning data using neural networks


Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization


LMFusion: Adapting Pretrained Language Models for Multimodal Generation


Generalization Bound of Gradient Flow through Training Trajectory and Data-dependent Kernel


The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models


pLSTM: parallelizable Linear Source Transition Mark networks


TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks


Inference-Time Hyper-Scaling with KV Cache Compression


Efficient Policy Optimization in Robust Constrained MDPs with Iteration Complexity Guarantees


Computational Algebra with Attention: Transformer Oracles for Border Basis Algorithms


AI-Researcher: Autonomous Scientific Innovation


Anti-Aliased 2D Gaussian Splatting


Multi-agent Markov Entanglement


The Emergence of Abstract Thought in Large Language Models Beyond Any Language


Synthetic Series-Symbol Data Generation for Time Series Foundation Models


Multiscale guidance of AlphaFold3 with heterogeneous cryo-EM data


Breaking the Frozen Subspace: Importance Sampling for Low-Rank Optimization in LLM Pretraining


FlyLoRA: Boosting Task Decoupling and Parameter Efficiency via Implicit
  Rank-Wise Mixture-of-Experts


Trained Mamba Emulates Online Gradient Descent in In-Context Linear Regression


Diffusion Beats Autoregressive in Data-Constrained Settings


An Investigation of Memorization Risk in Healthcare Foundation Models


MiCo: Multi-image Contrast for Reinforcement Visual Reasoning


Jailbreak-AudioBench: In-Depth Evaluation and Analysis of Jailbreak Threats for Large Audio Language Models


Single GPU Task Adaptation of Pathology Foundation Models for Whole Slide Image Analysis


Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models


ItDPDM: Information-Theoretic Discrete Poisson Diffusion Model


MEGADance: Mixture-of-Experts Architecture for Genre-Aware 3D Dance
  Generation


GUI Exploration Lab: Enhancing Screen Navigation in Agents via Multi-Turn Reinforcement Learning


OmniSync: Towards Universal Lip Synchronization via Diffusion Transformers


Among Us: A Sandbox for Measuring and Detecting Agentic Deception


Local Curvature Descent: Squeezing More Curvature out of Standard and Polyak Gradient Descent


GPSToken: Gaussian Parameterized Spatially-adaptive Tokenization for
  Image Representation and Generation


Dual-Stage Value-Guided Inference with Margin-Based Reward Adjustment for Fast and Faithful VLM Captioning


Approximately Aligned Decoding


OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding


A Physics-preserved Transfer Learning Method for Differential Equations


Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation


From Replication to Redesign: Exploring Pairwise Comparisons for LLM-Based Peer Review


Projecting Assumptions: The Duality Between Sparse Autoencoders and Concept Geometry


Delta Attention: Fast and Accurate Sparse Attention Inference by Delta Correction


Conformal Prediction for Time-series Forecasting with Change Points


An Efficient Local Search Approach for Polarized Community Discovery in Signed Networks


Global Prompt Refinement with Non-Interfering Attention Masking for One-Shot Federated Learning


Efficient Preference-Based Reinforcement Learning: Randomized Exploration meets Experimental Design


Vision-and-Language Training Helps Deploy Taxonomic Knowledge but Does Not Fundamentally Alter It


Which Data Attributes Stimulate Math and Code Reasoning? An Investigation via Influence Functions


Constrained Language Generation with Discrete Diffusion Models


PROFIT: A Specialized Optimizer for Deep Fine Tuning


ViewPoint: Panoramic Video Generation with Pretrained Diffusion Models


Demystifying Reasoning Dynamics with Mutual Information: Thinking Tokens are Information Peaks in LLM Reasoning


SpecReason: Fast and Accurate Inference-Time Compute via Speculative Reasoning


Audio-Sync Video Generation with Multi-Stream Temporal Control


G-Memory: Tracing Hierarchical Memory for Multi-Agent Systems


Personalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing


Reduction-based Pseudo-label Generation for Instance-dependent Partial Label Learning


GPAS: Accelerating Convergence of LLM Pretraining via   Gradient-Preserving Activation Scaling


VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Code


Inference-Time Text-to-Video Alignment with Diffusion Latent Beam Search


Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligence


Bivariate Matrix-valued Linear Regression (BMLR): Finite-sample performance under Identifiability and Sparsity Assumptions


How Many Tokens Do 3D Point Cloud Transformer Architectures Really Need?


True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics


Memory-Efficient Visual Autoregressive Modeling with Scale-Aware KV Cache Compression


Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size


Flexible MOF Generation with Torsion-Aware Flow Matching


SSTAG: Structure-Aware Self-Supervised Learning Method for Text-Attributed Graphs


Understanding Large Reasoning Models through Reasoning Graph Properties


Embedding Principle of Homogeneous Neural Network for Classification Problem


Neural Atlas Graphs for Dynamic Scene Decomposition and Editing


Variational Supervised Contrastive Learning


Compressed and Smooth Latent Space for Text Diffusion Modeling


Holistic Order Prediction in Natural Scenes


Point Cloud Synthesis Using Inner Product Transforms


StableGuard: Towards Unified Copyright Protection and Tamper Localization in Latent Diffusion Models


Localizing Knowledge in Diffusion Transformers


Learning Theory for Kernel Bilevel Optimization


Unifying Multitrack Music Arrangement via Reconstruction Fine-Tuning and Efficient Tokenization


When Are Concepts Erased From Diffusion Models?


One-Step Offline Distillation of Diffusion-based Models  via Koopman Modeling


Native-Resolution Image Synthesis


GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents


HyGen: Efficient LLM Serving via Elastic Online-Offline Request Co-location


A Minimalist Example of Edge-of-Stability and Progressive Sharpening


Señorita-2M: A High-Quality Instruction-based Dataset for General Video Editing by Video Specialists


Non-Stationary Lipschitz Bandits


Learning When to Think: Shaping Adaptive Reasoning in R1-Style Models via Multi-Stage RL


LibriBrain: Over 50 Hours of Within-Subject MEG to Improve Speech Decoding Methods at Scale


Metropolis Adjusted Microcanonical Hamiltonian Monte Carlo


TabArena: A Living Benchmark for Machine Learning on Tabular Data


Beyond Benign Overfitting in Nadaraya-Watson Interpolators


Fast MRI for All: Bridging Equity Gaps via Training without Raw Data Access


Continuous Subspace Optimization for Continual Learning


ConStellaration: A dataset of QI-like stellarator plasma boundaries and optimization benchmarks


MaintainCoder: Maintainable Code Generation Under Dynamic Requirements


BLEUBERI: BLEU is a surprisingly effective reward for instruction following


Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Tasks


InfiFPO: Implicit Model Fusion via Preference Optimization in Large Language Models


Paper2Poster: Towards Multimodal Poster Automation from Scientific Papers


Query Routing for Retrieval-Augmented Language Models


Preference-Guided Diffusion for Multi-Objective Offline Optimization


Jamais Vu: Exposing the Generalization Gap in Supervised Semantic Correspondence


Online Experimental Design With Estimation-Regret Trade-off Under Network Interference


ALTo: Adaptive-Length Tokenizer for Autoregressive Mask Generation


Likelihood-Ratio Regularized Quantile Regression: Adapting Conformal Prediction to High-Dimensional Covariate Shifts


Wukong's 72 Transformations: High-fidelity Textured 3D Morphing via Flow Models


Incremental Sequence Classification with Temporal Consistency


FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning


OVS Meets Continual Learning: Towards Sustainable Open-Vocabulary
  Segmentation


Structure Matters: Dynamic Policy Gradient


Boosting Generative Image Modeling via Joint Image-Feature Synthesis


Unveiling Environmental Sensitivity of Individual Gains in Influence Maximization


Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset


UVE: Are MLLMs Unified Evaluators for AI-Generated Videos?


Hybrid-Balance GFlowNet for Solving Vehicle Routing Problems


Signal and Noise: A Framework for Reducing Uncertainty in Language Model
  Evaluation


The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model


Grasp2Grasp: Vision-Based Dexterous Grasp Translation via Schrödinger Bridges


Efficiently Escaping Saddle Points under Generalized Smoothness via Self-Bounding Regularity


Measuring what Matters: Construct Validity in Large Language Model
  Benchmarks


Unleashing Hour-Scale Video Training for Long Video-Language Understanding


Exploring Diffusion Transformer Designs via Grafting


A-MEM: Agentic Memory for LLM Agents


A Data-Driven Prism: Multi-View Source Separation with Diffusion Model Priors


GeoRanker: Distance-Aware Ranking for Worldwide Image Geolocalization


Continuity and Isolation Lead to Doubts or Dilemmas in Large Language Models


Towards Resilient Safety-driven Unlearning for Diffusion Models against Downstream Fine-tuning


MoBA: Mixture of Block Attention for Long-Context LLMs


KVCOMM: Online Cross-context KV-cache Communication for Efficient
  LLM-based Multi-agent Systems


Simple and Effective Specialized Representations for Fair Classifiers


Stability and Sharper Risk Bounds with Convergence Rate $\tilde{O}(1/n^2)$


ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models


Last Iterate Convergence in Monotone Mean Field Games


HyRF: Hybrid Radiance Fields for Memory-efficient and High-quality Novel
  View Synthesis


Image Editing As Programs with Diffusion Models


UniZyme: A Unified Protein Cleavage Site Predictor Enhanced with Enzyme Active-Site Knowledge


Towards Comprehensive Scene Understanding: Integrating First and Third-Person Views for LVLMs


Matching Markets Meet LLMs: Algorithmic Reasoning with Ranked Preferences


On the Empirical Power of Goodness-of-Fit Tests in Watermark Detection


Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders


SHAP values via sparse Fourier representation


Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data


Preference-Based Dynamic Ranking Structure Recognition


Rethinking Approximate Gaussian Inference in Classification


Scalable Best-of-N Selection for Large Language Models via Self-Certainty


TalkCuts: A Large-Scale Dataset for Multi-Shot Human Speech Video Generation


FuncGenFoil: Airfoil Generation and Editing Model in Function Space


Assessing the quality of denoising diffusion models in Wasserstein distance: noisy score and optimal bounds


SteerConf: Steering LLMs for Confidence Elicitation


ReplaceMe: Network Simplification via Layer Pruning and Linear Transformations


Gatekeeper: Improving Model Cascades Through Confidence Tuning


UniGist: Towards General and Hardware-aligned Sequence-level Long
  Context Compression


Complexity Scaling Laws for Neural Models using Combinatorial Optimization


Protein Design with Dynamic Protein Vocabulary


Lifelong Safety Alignment for Language Models


CARES: Comprehensive Evaluation of Safety and Adversarial Robustness in Medical LLMs


Doctor Approved: Generating Medically Accurate Skin Disease Images through AI–Expert Feedback


Improved Bounds for Swap Multicalibration and Swap Omniprediction


Multidimensional Bayesian Utility Maximization: Tight Approximations to Welfare


DiffBreak: Is Diffusion-Based Purification Robust?


BikeBench: A Bicycle Design Benchmark for Generative Models with Objectives and Constraints


MathArena: Evaluating LLMs on Uncontaminated Math Competitions


Modeling Dynamic Neural Activity by combining Naturalistic Video Stimuli and Stimulus-independent Latent Factors


Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Models


Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry Priors


Asymptotics of SGD in Sequence-Single Index Models and Single-Layer Attention Networks


Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions


FlashBias: Fast Computation of Attention with Bias


Can Class-Priors Help Single-Positive Multi-Label Learning?


From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging


OmniFC: Rethinking Federated Clustering via Lossless and Secure Distance Reconstruction


Revisiting Logit Distributions for Reliable Out-of-Distribution Detection


MM-Agent: LLM as Agents for Real-world Mathematical Modeling Problem


Streaming Attention Approximation via Discrepancy Theory


State Entropy Regularization for Robust Reinforcement Learning


Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning


VideoUFO: A Million-Scale User-Focused Dataset for Text-to-Video Generation


Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values


On the Stability of Graph Convolutional Neural Networks: a Probabilistic Perspective


STaRFormer: Semi-Supervised Task-Informed Representation Learning via Dynamic Attention-Based Regional Masking for Sequential Data


Data Valuation using Neural Networks for Efficient Instruction Fine-Tuning


Distribution Learning Meets Graph Structure Sampling


Unveiling Transformer Perception by Exploring Input Manifolds


RoPECraft: Training-Free Motion Transfer with Trajectory-Guided RoPE Optimization on Diffusion Transformers


LinPrim: Linear Primitives for Differentiable Volumetric Rendering


Continuous Thought Machines


TrajAgent: An LLM-Agent Framework for Trajectory Modeling via Large-and-Small Model Collaboration


Neural Entropy


ImageSentinel: Protecting Visual Datasets from Unauthorized Retrieval-Augmented Image Generation


Unifying Attention Heads and Task Vectors via Hidden State Geometry in In-Context Learning


Approximate Domain Unlearning for Vision-Language Models


OmniTalker: Real-Time Text-Driven Talking Head Generation with In-Context Audio-Visual Style Replication


DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning


Alchemist: Turning Public Text-to-Image Data into Generative Gold


Many LLMs Are More Utilitarian Than One


Bridging Expressivity and Scalability with Adaptive Unitary SSMs


MIRAGE: A Benchmark for Multimodal Information-Seeking and Reasoning in
  Agricultural Expert-Guided Conversations


EchoShot: Multi-Shot Portrait Video Generation


Multi-scale Temporal Prediction via Incremental Generation and Multi-agent Collaboration


Multi-Scale Finetuning for Encoder-based Time Series Foundation Models


VQ-Seg: Vector-Quantized Token Perturbation for Semi-Supervised Medical Image Segmentation


From Noise to Narrative: Tracing the Origins of Hallucinations in   Transformers


Unleashing the Potential of Multimodal LLMs for Zero-Shot
  Spatio-Temporal Video Grounding


LightFair: Towards an Efficient Alternative for Fair T2I Diffusion via Debiasing Pre-trained Text Encoders


DitHub: A Modular Framework for Incremental Open-Vocabulary Object Detection


BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks and Defenses on Large Language Models


CQ-DINO: Mitigating Gradient Dilution via Category Queries for Vast Vocabulary Object Detection


Efficient Rectified Flow for Image Fusion


Native Segmentation Vision Transformers


Minimizing False-Positive Attributions in Explanations of Non-Linear Models


Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization


A Single-Loop Gradient Algorithm for Pessimistic Bilevel Optimization via Smooth Approximation


Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression


Breaking the Batch Barrier (B3) of Contrastive Learning via Smart Batch Mining


SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents


Optimizing Anytime Reasoning via Budget Relative Policy Optimization


Regression Trees Know Calculus


Sculpting Features from Noise: Reward-Guided Hierarchical Diffusion for Task-Optimal Feature Transformation


PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding


Breaking the Performance Ceiling in Complex Reinforcement Learning
  requires Inference Strategies


FocalCodec: Low-Bitrate Speech Coding via Focal Modulation Networks


Train to Defend: First Defense Against Cryptanalytic Neural Network Parameter Extraction Attacks


Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis


DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge


Efficient Quadratic Corrections for Frank-Wolfe Algorithms


Protein Inverse Folding From Structure Feedback


Can Large Language Models Master Complex Card Games?


Spectral Analysis of Representational Similarity with Limited Neurons


Theoretical Benefit and Limitation of Diffusion Language Model


Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based
  Diffusion Models


Carbon Aware Transformers Through Joint Model-Hardware Optimization


Mixture-of-Experts Meets In-Context Reinforcement Learning


CoT Information: Improved Sample Complexity under Chain-of-Thought
  Supervision


Personalized Subgraph Federated Learning with Differentiable Auxiliary Projections


Looking Beyond the Known: Towards a Data Discovery Guided Open-World Object Detection


Sekai: A Video Dataset towards World Exploration


NAUTILUS: A Large Multimodal Model for Underwater Scene Understanding


HybridNorm: Towards Stable and Efficient Transformer Training via Hybrid Normalization


Fairness-aware Anomaly Detection via Fair Projection


Open-ended Scientific Discovery via Bayesian Surprise


Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings


Seeing through Uncertainty: Robust Task-Oriented Optimization in Visual Navigation


Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting


Backdoor Cleaning without External Guidance in MLLM Fine-tuning


Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs


A Temporal Difference Method for Stochastic Continuous Dynamics


RODS: Robust Optimization Inspired Diffusion Sampling for Detecting and Reducing Hallucination in Generative Models


A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning


The Cost of Compression: Tight Quadratic Black-Box Attacks on Sketches for $\ell_2$ Norm Estimation


VideoLucy: Deep Memory Backtracking for Long Video Understanding


CLIMB: CLustering-based Iterative Data Mixture Bootstrapping for Language Model Pre-training


NFIG: Autoregressive Image Generation with Next-Frequency Prediction


SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding


WhAM: Towards A Translative Model of Sperm Whale Vocalization


Towards Provable Emergence of In-Context Reinforcement Learning


MetaMind: Modeling Human Social Thoughts with Metacognitive Multi-Agent Systems


JailBound: Jailbreaking Internal Safety Boundaries of Vision-Language Models


On scalable and efficient training of diffusion samplers


Bandit and Delayed Feedback in Online Structured Prediction


Prot2Text-V2: Protein Function Prediction with Multimodal Contrastive
  Alignment


FRN: Fractal-Based Recursive Spectral Reconstruction Network


A Unifying View of Linear Function Approximation in Off-Policy RL Through Matrix Splitting and Preconditioning


AcuRank: Uncertainty-Aware Adaptive Computation for Listwise Reranking


Seeing What Matters: Generalizable AI-generated Video Detection with Forensic-Oriented Augmentation


Boosting Adversarial Transferability with Spatial Adversarial Alignment


Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means


Dynamical Decoupling of Generalization and Overfitting in Large Two-Layer Networks


Generating Multi-Table Time Series EHR from Latent Space with Minimal Preprocessing


Preserving Task-Relevant Information Under Linear Concept Removal


Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model


Training-Free Constrained Generation With Stable Diffusion Models


The Overthinker's DIET: Cutting Token Calories with DIfficulty-AwarE Training


Robust LLM Alignment via Distributionally Robust Direct Preference Optimization


Emergence of Linear Truth Encodings in Language Models


Efficient Part-level 3D Object Generation via Dual Volume Packing


DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation Trainer


Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates


Non-Asymptotic Analysis Of Data Augmentation For Precision Matrix Estimation


Optimal Neural Compressors for the Rate-Distortion-Perception Tradeoff


Self-Supervised Learning of Motion Concepts by Optimizing Counterfactuals


un$^2$CLIP: Improving CLIP's Visual Detail Capturing Ability via Inverting unCLIP


FreqPolicy: Efficient Flow-based Visuomotor Policy via Frequency Consistency


Vision Function Layer in Multimodal LLMs


The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements


Large language models can learn and generalize steganographic chain-of-thought under process supervision


IllumiCraft: Unified Geometry and Illumination Diffusion for Controllable Video Generation


Conditional Panoramic Image Generation via Masked Autoregressive Modeling


SATURN: SAT-based Reinforcement Learning to Unleash Language Model Reasoning


MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval


AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning


Enhancing LLM Watermark Resilience Against Both Scrubbing and  Spoofing Attacks


On the Existence and Complexity of Core-Stable Data Exchanges


ELECTRA: A Cartesian Network for 3D Charge Density Prediction with Floating Orbitals


BridgePure: Limited Protection Leakage Can Break Black-Box Data Protection


ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference


ARGenSeg: Image Segmentation with Autoregressive Image Generation Model


ProtInvTree: Deliberate Protein Inverse Folding with Reward-guided Tree Search


RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics


Top-H Decoding: Adapting the Creativity and Coherence with Bounded
  Entropy in Text Generation


AR-RAG: Autoregressive Retrieval Augmentation for Image Generation


A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference


Unveiling Concept Attribution in Diffusion Models


Optimal Rates  for Generalization of Gradient Descent for Deep ReLU Classification


Lorentz Local Canonicalization: How to make any Network Lorentz-Equivariant


Efficient Federated Learning against Byzantine Attacks and Data Heterogeneity via Aggregating Normalized Gradients


Lyapunov-Stable Adaptive Control for Multimodal Concept Drift


GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning


Table as a Modality for Large Language Models


Escaping Collapse: The Strength of Weak Data for Large Language Model Training


Can DPO Learn Diverse Human Values? A Theoretical Scaling Law


A Unified Reasoning Framework for Holistic Zero-Shot Video Anomaly Analysis


Instant4D: 4D Gaussian Splatting in Minutes


UrbanDiT: A Foundation Model for Open-World Urban Spatio-Temporal Learning


Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search


Why Knowledge Distillation Works in Generative Models: A Minimal Working Explanation


Scalable Graph Generative Modeling via Substructure Sequences


KGGen: Extracting Knowledge Graphs from Plain Text with Language Models


Enhancing Text-to-Image Diffusion Transformer via Split-Text Conditioning


SDTagNet: Leveraging Text-Annotated Navigation Maps for Online HD Map Construction


Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data


Broken Tokens? Your Language Model can Secretly Handle Non-Canonical Tokenizations


E-MoFlow: Learning Egomotion and Optical Flow from Event Data via Implicit Regularization


Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models


Packing Input Frame Context in Next-Frame Prediction Models for Video Generation


Tight Bounds on the Distortion of Randomized and Deterministic Distributed Voting


VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning


Breaking Latent Prior Bias in Detectors for Generalizable AIGC Image
  Detection


Towards Unified Latent Space for 3D Molecular Latent Diffusion Modeling


A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning


Inference-Time Scaling for Flow Models via Stochastic Generation and Rollover Budget Forcing


OmniBench: Towards The Future of Universal Omni-Language Models


LiveStar: Live Streaming Assistant for Real-World Online Video Understanding


Aux-Think: Exploring Reasoning Strategies for Data-Efficient
  Vision-Language Navigation


When Additive Noise Meets Unobserved Mediators: Bivariate Denoising Diffusion for Causal Discovery


Alignment of Large Language Models with Constrained Learning


3D Interaction Geometric Pre-training for Molecular Relational Learning


Amortized Variational Transdimensional Inference


Understanding the Evolution of the Neural Tangent Kernel at the Edge of Stability


Finite Sample Analyses for Continuous-time Linear Systems: System Identification and Online Control


Straight-Line Diffusion Model for Efficient 3D Molecular Generation


CoDA: Coordinated Diffusion Noise Optimization for Whole-Body Manipulation of Articulated Objects


SubTrack++ : Gradient Subspace Tracking for Scalable LLM Training


Self Iterative Label Refinement via Robust Unlabeled Learning


Conditional Representation Learning for Customized Tasks


Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback


PanTS: The Pancreatic Tumor Segmentation Dataset


Private Continual Counting of Unbounded Streams


PairEdit: Learning Semantic Variations for Exemplar-based Image Editing


Scaling Embedding Layers in Language Models


ODG: Occupancy Prediction Using Dual Gaussians


Dimension-free Score Matching and Time Bootstrapping for Diffusion Models


Plug-and-Play Context Feature Reuse for Efficient Masked Generation


Is PRM Necessary? Problem-Solving RL Implicitly Induces PRM Capability in LLMs


Statistical Inference for Gradient Boosting Regression


ObCLIP: Oblivious CLoud-Device Hybrid Image Generation with Privacy Preservation


RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning


Repo2Run: Automated Building Executable Environment for Code Repository at Scale


Token Dynamics: Towards Efficient and Dynamic Video Token Representation for Video Large Language Models


Thompson Sampling in Function Spaces via Neural Operators


Qsharp: Provably Optimal Distributional RL for LLM Post-Training


seq-JEPA: Autoregressive Predictive Learning of Invariant-Equivariant World Models


The Mirage of Performance Gains: Why Contrastive Decoding Fails to Mitigate Object Hallucinations in MLLMs?


Vision-centric Token Compression in Large Language Model


ThermalGen: Style-Disentangled Flow-Based Generative Models for
  RGB-to-Thermal Image Translation


Understanding while Exploring: Semantics-driven Active Mapping


DynamicVL: Benchmarking Multimodal Large Language Models for Dynamic
  City Understanding


Teaching Language Models to Evolve with Users: Dynamic Profile Modeling for Personalized Alignment


Learning to Learn with Contrastive Meta-Objective


Fairshare Data Pricing via Data Valuation for Large Language Models


InternScenes: A Large-scale Simulatable Indoor Scene Dataset with   Realistic Layouts


How to build a consistency model: Learning flow maps via self-distillation


Real-Time Execution of Action Chunking Flow Policies


FOCUS: Unified Vision-Language Modeling for Interactive Editing Driven
  by Referential Segmentation


Transformers Learn Faster with Semantic Focus


Bisecle: Binding and Separation in Continual Learning for Video Language Understanding


Why Masking Diffusion Works: Condition on the Jump Schedule for Improved Discrete Diffusion


Optimality of the Median-of-Means Estimator under Adversarial Contamination


AceSearcher: Bootstrapping Reasoning and Search for LLMs via Reinforced
  Self-Play


Semi-Supervised Regression with Heteroscedastic Pseudo-Labels


4D-VLA: Spatiotemporal Vision-Language-Action Pretraining with
  Cross-Scene Calibration


SD-VLM: Spatial Measuring and Understanding with Depth-Encoded Vision-Language Models


Over-squashing in Spatiotemporal Graph Neural Networks


Transfer Learning on Edge Connecting Probability Estimation Under Graphon Model


Linear Transformers Implicitly Discover Unified Numerical Algorithms


Model Provenance Testing for Large Language Models


FastDINOv2: Frequency Based Curriculum Learning Improves Robustness and
  Training Speed


Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks


Practical Bayes-Optimal Membership Inference Attacks


From Flat to Hierarchical: Extracting Sparse Representations with
  Matching Pursuit


MagCache: Fast Video Generation with Magnitude-Aware Cache


InfantAgent-Next: A Multimodal Generalist Agent for Automated Computer Interaction


Talk2Event: Grounded Understanding of Dynamic Scenes from Event Cameras


CodeGEMM: A Codebook-Centric Approach to Efficient GEMM in Quantized LLMs


Constrained Diffusers for Safe Planning and Control


PARTONOMY: Large Multimodal Models with Part-Level Visual Understanding


RAT: Bridging RNN Efficiency and Attention Accuracy in Language Modeling


OpenBox: Annotate Any Bounding Boxes in 3D


SAS: Simulated Attention Score


Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning


OverLayBench: A Benchmark for Layout-to-Image Generation with Dense
  Overlaps


Infinite-Width Limit of a Single Attention Layer: Analysis via Tensor Programs


Why and How LLMs Hallucinate: Connecting the Dots with Subsequence Associations


Scaling Code-Assisted Chain-of-Thoughts and Instructions for Model
  Reasoning


Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search


PartCrafter: Structured 3D Mesh Generation via Compositional Latent   Diffusion Transformers


OpenWorldSAM: Extending SAM2 for Universal Image Segmentation with Language Prompts


DynaAct: Large Language Model Reasoning with Dynamic Action Spaces


A compressive-expressive communication framework for compositional representations


FedEL: Federated Elastic Learning for Heterogeneous Devices


Risk Bounds For Distributional Regression


Autonomous Behavior and Whole-Brain Dynamics Emerge in Embodied Zebrafish Agents with Model-based Intrinsic Motivation


On the Convergence of Single-Timescale Actor-Critic


DreamLight: Towards Harmonious and Consistent Image Relighting


Learning Individual Behavior in Agent-Based Models with Graph Diffusion Networks


Learning Provably Improves the Convergence of Gradient Descent


Mixture of Scope Experts at Test: Generalizing Deeper Graph Neural Networks with Shallow Variants


Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior


GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation


AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning


Which Algorithms Have Tight Generalization Bounds?


Scalable In-context Ranking with Generative Models


PhysDrive: A Multimodal Remote Physiological Measurement Dataset for
  In-vehicle Driver Monitoring


UMoE: Unifying Attention and FFN with Shared Experts


Q-Insight: Understanding Image Quality via Visual Reinforcement Learning


Parameterized Synthetic Text Generation with SimpleStories


Inexact Column Generation for Bayesian Network Structure Learning via Difference-of-Submodular Optimization


Acceleration via silver step-size on Riemannian manifolds with applications to Wasserstein space


AuroRA: Breaking Low-Rank Bottleneck of LoRA with Nonlinear Mapping


Non-Adaptive Adversarial Face Generation


One-Step Diffusion-Based Image Compression with Semantic Distillation


Program Synthesis via Test-Time Transduction


Causal LLM Routing: End-to-End Regret Minimization from Observational Data


Multipole Attention for Efficient Long Context Reasoning


QoQ-Med: Building Multimodal Clinical Foundation Models with
  Domain-Aware GRPO Training


AltLoRA: Towards Better Gradient Approximation in Low-Rank Adaptation with Alternating Projections


Text to Sketch Generation with Multi-Styles


Towards Reliable Identification of Diffusion-based Image Manipulations


EnerVerse: Envisioning Embodied Future Space for Robotics Manipulation


ModHiFi: Identifying High Fidelity predictive components for Model Modification


Path-specific effects for pulse-oximetry guided decisions in critical care


Graph Your Own Prompt


Ambient Diffusion Omni: Training Good Models with Bad Data


Stochastic Process Learning via Operator Flow Matching


Emergence and scaling laws in SGD learning of shallow neural networks


Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modeling


A Unified Analysis of Stochastic Gradient Descent with Arbitrary Data Permutations and Beyond


LTD-Bench: Evaluating Large Language Models by Letting Them Draw


Adaptive Batch-Wise Sample Scheduling for Direct Preference Optimization


Uncovering the Spectral Bias in Diagonal State Space Models


When Less Language is More: Language-Reasoning Disentanglement Makes LLMs Better Multilingual Reasoners


Nonlinearly Preconditioned Gradient Methods: Momentum and Stochastic Analysis


A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning


ShorterBetter: Guiding Reasoning Models to Find Optimal Inference Length for Efficient Reasoning


MigGPT: Harnessing Large Language Models for Automated Migration of Out-of-Tree Linux Kernel Patches Across Versions


Know What You Don't Know: Uncertainty Calibration of Process Reward
  Models


Memory Mosaics at scale


Local-Global Associative Frames for Symmetry-Preserving Crystal Structure Modeling


Implicit Bias of Spectral Descent and Muon on Multiclass Separable Data


FSNet: Feasibility-Seeking Neural Network for Constrained Optimization with Guarantees


RULE: Reinforcement UnLEarning Achieves Forget-retain Pareto Optimality


DAMamba: Vision State Space Model with Dynamic Adaptive Scan


MoPFormer: Motion-Primitive Transformer for Wearable-Sensor Activity Recognition


Sloth: scaling laws for LLM skills to predict multi-benchmark performance across families


Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries


VLMLight: Safety-Critical Traffic Signal Control via Vision-Language Meta-Control and Dual-Branch Reasoning Architecture


Multi-Objective Hyperparameter Selection via Hypothesis Testing on Reliability Graphs


Efficient Fairness-Performance Pareto Front Computation


All that structure matches does not glitter


PLEIADES: Building Temporal Kernels with Orthogonal Polynomials


MoME: Mixture of Matryoshka Experts for Audio-Visual Speech Recognition


SAFE: Multitask Failure Detection for Vision-Language-Action Models


Spectral Convolutional Conditional Neural Processes


Exact and Linear Convergence for Federated Learning under Arbitrary Client Participation is Attainable


SonoGym: High Performance Simulation for Challenging Surgical Tasks with
  Robotic Ultrasound


Learning the Plasticity: Plasticity-Driven Learning Framework in Spiking Neural Networks


Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL


Automated Composition of Agents: A Knapsack Approach for Agentic
  Component Selection


A Closer Look at Model Collapse: From a Generalization-to-Memorization Perspective


TempSamp-R1: Effective Temporal Sampling with Reinforcement Fine-Tuning
  for Video LLMs


VolleyBots: A Testbed for Multi-Drone Volleyball Game Combining Motion
  Control and Strategic Play


Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models


BrainOmni: A Brain Foundation Model for Unified EEG and MEG Signals


Flow-GRPO: Training Flow Matching Models via Online RL


Sequential Monte Carlo for Policy Optimization in Continuous POMDPs


EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models


HetSyn: Versatile Timescale Integration in Spiking Neural Networks via Heterogeneous Synapses


Generator-Mediated Bandits: Thompson Sampling for GenAI-Powered Adaptive Interventions


Autoregressive Adversarial Post-Training for Real-Time Interactive Video   Generation


Knowing When to Stop: Dynamic Context Cutoff for Large Language Models


Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach


Next Semantic Scale Prediction via Hierarchical Diffusion Language Models


From Condensation to Rank Collapse: A Two-Stage Analysis of Transformer Training Dynamics


Eliciting Reasoning in Language Models with Cognitive Tools


APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning


Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning


Training-Free Bayesianization for Low-Rank Adapters of Large Language Models


Learn2Mix: Training Neural Networks Using Adaptive Data Integration


UniTraj: Learning a Universal Trajectory Foundation Model from Billion-Scale Worldwide Traces


FerretNet: Efficient Synthetic Image Detection via Local Pixel Dependencies


Self-alignment of Large Video Language Models with Refined Regularized Preference Optimization


Demystifying Spectral Feature Learning for Instrumental Variable Regression


Channel Simulation and Distributed Compression with Ensemble Rejection Sampling


LLM-driven Indoor Scene Layout Generation via Scaled Human-aligned Data Synthesis and Multi-Stage Preference Optimization


4DGT: Learning a 4D Gaussian Transformer Using Real-World Monocular Videos


SimulMEGA: MoE Routers are Advanced Policy Makers for Simultaneous Speech Translation


How Does Sequence Modeling Architecture Influence Base Capabilities of Pre-trained Language Models? Exploring Key Architecture Design Principles to Avoid Base Capabilities Degradation


Bohdi: Heterogeneous LLM Fusion with Automatic Data Exploration


On the Hardness of Approximating Distributions with Probabilistic Circuits


Model Selection for Off-policy Evaluation: New Algorithms and Experimental Protocol


PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts


Reinforcement Learning for Out-of-Distribution Reasoning in LLMs: An Empirical Study on Diagnosis-Related Group Coding


NSNQuant: A Double Normalization Approach for Calibration-Free Low-Bit Vector Quantization of KV Cache


SPACE: SPike-Aware Consistency Enhancement for Test-Time Adaptation in Spiking Neural Networks


Quartet: Native FP4 Training Can Be Optimal for Large Language Models


Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning


AgentAuditor: Human-level Safety and Security Evaluation for LLM Agents


Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points


ROGR: Relightable 3D Objects using Generative Relighting


The third pillar of causal analysis? A measurement perspective on causal representations


OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics


Self-Verifying Reflection Helps Transformers with CoT Reasoning


HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages


Neural Collapse is Globally Optimal in Deep Regularized ResNets and Transformers


Revisiting Frank-Wolfe for Structured Nonconvex Optimization


Uni-LoRA: One Vector is All You Need


LUNAR: LLM Unlearning via Neural Activation Redirection


On the Surprising Effectiveness of Large Learning Rates under Standard Width Scaling


GraSS: Scalable Influence Function with Sparse Gradient Compression


Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models


Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples


Safety Pretraining: Toward the Next Generation of Safe AI


Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning


Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks


DynaGuide: Steering Diffusion Polices with Active Dynamic Guidance


What Expressivity Theory Misses: Message Passing Complexity for GNNs


Spurious-Aware Prototype Refinement for Reliable Out-of-Distribution Detection


LARGO: Latent Adversarial Reflection through Gradient Optimization for Jailbreaking LLMs


Matryoshka: Learning to Drive Black-Box LLMs with LLMs


Pool Me Wisely: On the Effect of Pooling in Transformer-Based Models


Ascent Fails to Forget


Active Test-time Vision-Language Navigation


SpatialLM: Training Large Language Models for Structured Indoor Modeling


Neural Mutual Information Estimation with Vector Copulas


Resolution of Simpson's paradox via the common cause principle


Fixed-Point RNNs: Interpolating from Diagonal to Dense


Understanding Generalization in Physics Informed Models through Affine Variety Dimensions


InstructRestore: Region-Customized Image Restoration with Human
  Instructions


A Frustratingly Simple Yet Highly Effective Attack Baseline: Over 90% Success Rate Against the Strong Black-box Models of GPT-4.5/4o/o1


OS-Harm: A Benchmark for Measuring Safety of Computer Use Agents


Differential Privacy for Euclidean Jordan Algebra with Applications to Private Symmetric Cone Programming


AVROBUSTBENCH: Benchmarking the Robustness of Audio-Visual
  Recognition Models at Test-Time


Omni-R1: Reinforcement Learning for Omnimodal Reasoning via Two-System Collaboration


TTS-VAR: A Test-Time Scaling Framework for Visual Auto-Regressive   Generation


S$^2$NN: Sub-bit Spiking Neural Networks


SegMASt3R: Geometry Grounded Segment Matching


Harnessing the Universal Geometry of Embeddings


QuadEnhancer: Leveraging Quadratic Transformations to Enhance Deep Neural Networks


Tight Generalization Bounds for Large-Margin Halfspaces


DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning with Dual-Pathway Global-Local Fusion


Time-IMM: A Dataset and Benchmark for Irregular Multimodal Multivariate
  Time Series


Safe RLHF-V: Safe Reinforcement Learning from Human Feedback in Multimodal Large Language Models


Parameter Efficient Fine-tuning via Explained Variance Adaptation


WorldWeaver: Generating Long-Horizon Video Worlds via Rich Perception


AlignAb: Pareto-Optimal Energy Alignment for Designing Nature-Like Antibodies


Group-in-Group Policy Optimization for LLM Agent Training


Exploring the Noise Robustness of Online Conformal Prediction


RobIA: Robust Instance-aware Continual Test-time Adaptation for Deep Stereo


Novel View Synthesis from A Few Glimpses via Test-Time Natural Video Completion


Hogwild! Inference: Parallel LLM Generation via Concurrent Attention


Learning Shared Representations from Unpaired Data


Handling Label Noise via Instance-Level Difficulty Modeling and Dynamic Optimization


Fast Training of Large Kernel Models with Delayed Projections


PhysGym: Benchmarking LLMs in Interactive Physics Discovery with   Controlled Priors


SensorLM: Learning the Language of Wearable Sensors


Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality


From Average-Iterate to Last-Iterate Convergence in Games: A Reduction and Its Applications


Nested Learning: The Illusion of Deep Learning Architectures


Covariate-moderated Empirical Bayes Matrix Factorization


Long-Tailed Recognition via Information-Preservable Two-Stage Learning


SAMA: Towards Multi-Turn Referential Grounded Video Chat with Large Language Models


PSI: A Pedestrian Behavior Dataset for Socially Intelligent Autonomous Car


Provably Efficient RL under Episode-Wise Safety in Constrained MDPs with Linear Function Approximation


TITAN: A Trajectory-Informed Technique for Adaptive Parameter Freezing in Large-Scale VQE


Learning to Instruct for Visual Instruction Tuning


Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusion


Adaptive Classifier-Free Guidance via Dynamic Low-Confidence Masking


Show-o2: Improved Native Unified Multimodal Models


Embodied Web Agents: Bridging Physical-Digital Realms for Integrated Agent Intelligence


Adversarial Paraphrasing: A Universal Attack for Humanizing AI-Generated Text


End-to-End Vision Tokenizer Tuning


AmorLIP: Efficient Language-Image Pretraining via Amortization


QuadricFormer: Scene as Superquadrics for 3D Semantic Occupancy Prediction


OnlineSplatter: Pose-Free Online 3D Reconstruction for Free-Moving
  Objects


GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Driving


PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation


Meta CLIP 2: A Worldwide Scaling Recipe


Fine-grained List-wise Alignment for Generative Medication Recommendation


Exploring the Design Space of Diffusion Bridge Models


S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models


Fast constrained sampling in pre-trained diffusion models


Brain network science modelling of sparse neural networks enables Transformers and LLMs to perform as fully connected


Seeing the Wind from a Falling Leaf


Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning


Continual Multimodal Contrastive Learning


REGen: Multimodal Retrieval-Embedded Generation for Long-to-Short Video Editing


Transferring Features Across Language Models With Model Stitching


Audio Super-Resolution with Latent Bridge Models


Structure-Aware Spectral Sparsification via Uniform Edge Sampling


A Generalized Bisimulation Metric of State Similarity between Markov Decision Processes: From Theoretical Propositions to Applications


Masked Diffusion Models as Energy Minimization


BEDLAM2.0: Synthetic Humans and Cameras in Motion


Advancing Expert Specialization for Better MoE


Exploring Polyglot Harmony: On Multilingual Data Allocation for  Large Language Models Pretraining


How Well Can Differential Privacy Be Audited in One Run?


URSA: Understanding and Verifying Chain-of-thought Reasoning in Multimodal Mathematics


CodeMerge: Codebook-Guided Model Merging for Robust Test-Time Adaptation in Autonomous Driving


Generalizing Verifiable Instruction Following


GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations


MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks


Mellow: a small audio language model for reasoning


Video World Models with Long-term Spatial Memory


PolyVivid: Vivid Multi-Subject Video Generation with Cross-Modal Interaction and Enhancement


Cost-Efficient LLM Training with Lifetime-Aware Tensor Offloading via GPUDirect Storage


Towards Predicting Any Human Trajectory In Context


WORLDMEM: Long-term Consistent World Simulation with Memory


OrbitZoo: Real Orbital Systems Challenges for Reinforcement Learning


RAST: Reasoning Activation in LLMs via Small-model Transfer


A kernel conditional two-sample test


Point or Line? Using Line-based Representation for Panoptic Symbol Spotting in CAD Drawings


Inst-IT: Boosting Multimodal Instance Understanding via Explicit Visual Prompt Instruction Tuning


SymRTLO: Enhancing RTL Code Optimization with LLMs and Neuron-Inspired Symbolic Reasoning


STRATUS: A Multi-agent System for Autonomous Reliability Engineering of Modern Clouds


Robust Neural Rendering in the Wild with Asymmetric Dual 3D Gaussian   Splatting


Enhancing Interpretability in Deep Reinforcement Learning through
  Semantic Clustering


Controllable Human-centric Keyframe Interpolation with Generative Prior


Transferable Black-Box One-Shot Forging of Watermarks via Image
  Preference Models


Robust Satisficing Gaussian Process Bandits Under Adversarial Attacks


High-Dimensional Calibration from Swap Regret


SwitchLingua: The First Large-Scale Multilingual and Multi-Ethnic
  Code-Switching Dataset


Collective Counterfactual Explanations: Balancing Individual Goals and Collective Dynamics


World-aware Planning Narratives Enhance Large Vision-Language Model Planner


Large Language Diffusion Models


The Gaussian Mixing Mechanism: Differential Privacy via Gaussian Sketches


ARM: Adaptive Reasoning Model


Stable Port-Hamiltonian Neural Networks


NeuralSurv: Deep Survival Analysis with Bayesian Uncertainty Quantification


OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation


This Time is Different: An Observability Perspective on Time Series Foundation Models


A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging


Quantifying Uncertainty in Error Consistency: Towards Reliable Behavioral Comparison of Classifiers


Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings


Adversarial Graph Fusion for Incomplete Multi-view Semi-supervised Learning with Tensorial Imputation


Representation Consistency for Accurate and Coherent LLM Answer Aggregation


HYPRL: Reinforcement Learning of Control Policies for Hyperproperties


Value Improved Actor Critic Algorithms


Bidirectional Representations Augmented Autoregressive Biological
  Sequence Generation:Application in De Novo Peptide Sequencing


MuSLR: Multimodal Symbolic Logical Reasoning


Accelerating Visual-Policy Learning through Parallel Differentiable Simulation


Grids Often Outperform Implicit Neural Representations


Adaptive Defense against Harmful Fine-Tuning for Large Language Models via Bayesian Data Scheduler


Integration Matters for Learning PDEs with Backwards SDEs


WritingBench: A Comprehensive Benchmark for Generative Writing


ScatterAD: Temporal-Topological Scattering Mechanism for Time Series Anomaly Detection


BlurDM: A Blur Diffusion Model for Image Deblurring


Orient Anything V2: Unifying Orientation and Rotation Understanding


Incentivizing Truthful Language Models via Peer Elicitation Games


Dynamic Risk Assessments for Offensive Cybersecurity Agents


Thumb on the Scale: Optimal Loss Weighting in Last Layer Retraining


The Complexity of Finding Local Optima in Contrastive Learning


Accelerating Diffusion LLMs via Adaptive Parallel Decoding


HAODiff: Human-Aware One-Step Diffusion via Dual-Prompt Guidance


DAVE: Diagnostic benchmark for Audio Visual Evaluation


ConfTuner: Training Large Language Models to Express Their Confidence
  Verbally


ReID5o: Achieving Omni Multi-modal Person Re-identification in a Single Model


A Tale of Two Symmetries: Exploring the Loss Landscape of Equivariant Models


How to Train Your LLM Web Agent: A Statistical Diagnosis


Wavelet Canonical Coherence for Nonstationary Signals


Who Speaks for the Trigger? Dynamic Expert Routing in Backdoored Mixture-of-Experts Transformers


ReMindRAG: Low-Cost LLM-Guided Knowledge Graph Traversal for Efficient RAG


FlowMoE: A Scalable Pipeline Scheduling Framework for Distributed Mixture-of-Experts Training


SageAttention3: Microscaling FP4 Attention for Inference and An Exploration of 8-Bit Training


MVU-Eval: Towards Multi-Video Understanding Evaluation for Multimodal
  LLMs


On Extending Direct Preference Optimization to Accommodate Ties


Fairness under Competition


SCAN: Self-Denoising Monte Carlo Annotation for Robust Process Reward
  Learning


ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition


Decomposing stimulus-specific sensory neural information via diffusion models


CineTechBench: A Benchmark for Cinematographic Technique Understanding and Generation


On Hierarchies of Fairness Notions in Cake Cutting: From Proportionality to Super Envy-Freeness


From Judgment to Interference: Early Stopping LLM Harmful Outputs via Streaming Content Monitoring


Speculate Deep and Accurate: Lossless and Training-Free Acceleration for Offloaded LLMs via Substitute Speculative Decoding


RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval


Neuro-Spectral Architectures for Causal Physics-Informed Networks


FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Design


PurpCode: Reasoning for Safer Code Generation


Pragmatic Heterogeneous Collaborative Perception via Generative Communication Mechanism


Predictive Preference Learning from Human Interventions


Tracing the Representation Geometry of Language Models from Pretraining to Post-training


Learning Stochastic Multiscale Models


Attention (as Discrete-Time Markov) Chains


Feedback Friction: LLMs Struggle to Fully Incorporate External Feedback


Scalable Exploration via Ensemble++


Controlling the Spread of Epidemics on Networks with Differential
  Privacy


What Happens During the Loss Plateau? Understanding Abrupt Learning in Transformers


System Prompt Optimization with Meta-Learning


A Principled Approach to Randomized Selection under Uncertainty


Adv-BMT: Bidirectional Motion Transformer for Safety-Critical Traffic
  Scenario Generation


Revisiting Glorot Initialization for Long-Range Linear Recurrences


CamSAM2: Segment Anything Accurately in Camouflaged Videos


Scale leads to compositional generalization


Class-aware Domain Knowledge Fusion and Fission for Continual Test-Time Adaptation


Foundation Models for Scientific Discovery: From Paradigm Enhancement to
  Paradigm Transition


Interpreting vision transformers via residual replacement model


Object-centric 3D Motion Field for Robot Learning from Human Videos


Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking


RadZero: Similarity-Based Cross-Attention for Explainable Vision-Language Alignment in Radiology with Zero-Shot Multi-Task Capability


BTL-UI: Blink-Think-Link Reasoning Model for GUI Agent


Geometry Meets Incentives: Sample-Efficient Incentivized Exploration with Linear Contexts


DiEP: Adaptive Mixture-of-Experts Compression through Differentiable Expert Pruning


General-Reasoner: Advancing LLM Reasoning Across All Domains


Kernel Regression in Structured Non-IID Settings: Theory and Implications for Denoising Score Learning


KARMA: Leveraging Multi-Agent LLMs for Automated Knowledge Graph Enrichment


FreqPolicy: Frequency Autoregressive Visuomotor Policy with Continuous
  Tokens


The Logical Expressiveness of Temporal GNNs via Two-Dimensional Product Logics


Vision Transformers Don't Need Trained Registers


Towards Fully FP8 GEMM LLM Training at Scale


d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning


COCONut-PanCap: Joint Panoptic Segmentation and Grounded Captions for Fine-Grained Understanding and Generation


The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text


SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning


Advancing Compositional Awareness in CLIP with Efficient Fine-Tuning


REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards


Uni-Instruct: One-step Diffusion Model through Unified Diffusion Divergence Instruction


VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning


Adaptive Algorithms with Sharp Convergence Rates for Stochastic Hierarchical Optimization


DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization


Continual Release Moment Estimation with Differential Privacy


DISCO: Disentangled Communication Steering for Large Language Models


GeoVideo: Introducing Geometric Regularization into Video Generation Model


TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning


Spiral: Semantic-Aware Progressive LiDAR Scene Generation


ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs


SYMPHONY: Synergistic Multi-agent Planning with Heterogeneous Language Model Assembly


MSTAR: Box-free Multi-query Scene Text Retrieval with Attention Recycling


Pairwise Calibrated Rewards for Pluralistic Alignment


SafePTR: Token-Level Jailbreak Defense in Multimodal LLMs via Prune-then-Restore Mechanism


Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment


RGB-Only Supervised Camera Parameter Optimization in Dynamic Scenes


The quest for the GRAph Level autoEncoder (GRALE)


Prompt Tuning Decision Transformers with Structured and Scalable Bandits


AlphaFold Database Debiasing for Robust Inverse Folding


AlphaZero Neural Scaling and Zipf's Law: a Tale of Board Games and Power Laws


PALQO: Physics-informed model for Accelerating  Large-scale Quantum Optimization


Process vs. Outcome Reward: Which is Better for Agentic RAG Reinforcement Learning


rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset


Reward-Aware Proto-Representations in Reinforcement Learning


Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space


Spot the Fake: Large Multimodal Model-Based Synthetic Image Detection   with Artifact Explanation


Preference Optimization by Estimating the Ratio of the Data Distribution


Lookahead Routing for Large Language Models


Corrector Sampling in Language Models


Iterative Tool Usage Exploration for Multimodal Agents via Step-wise Preference Tuning


DeceptionBench: A Comprehensive Benchmark for AI Deception Behaviors in Real-world Scenarios


What Makes a Reward Model a Good Teacher? An Optimization Perspective


Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection


Revisiting Semi-Supervised Learning in the Era of Foundation Models


Ada-R1: Hybrid-CoT via Bi-Level Adaptive Reasoning Optimization


Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry


Continuous Simplicial Neural Networks


Density Ratio-Free Doubly Robust Proxy Causal Learning


Maximizing the Value of Predictions in Control: Accuracy Is Not Enough


Ranking-based Preference Optimization for Diffusion Models from Implicit
  User Feedback


FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large
  Language Models


CAD-Coder: Text-to-CAD Generation with Chain-of-Thought and Geometric
  Reward


Unlocking Aha Moments via Reinforcement Learning: Advancing Collaborative Visual Comprehension and Generation


Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning


Chain-of-Retrieval Augmented Generation


Constrained Sampling for Language Models Should Be Easy: An MCMC Perspective


Mitigating Hallucination in VideoLLMs via Temporal-Aware Activation Engineering


RGNMR: A Gauss-Newton method for robust matrix completion with theoretical guarantees


Multi-Token Prediction Needs Registers


Hierarchical Frequency Tagging Probe (HFTP): A Unified Approach to
  Investigate Syntactic Structure Representations in Large Language Models and
  the Human Brain


Rendering-Aware Reinforcement Learning for Vector Graphics Generation


Rethinking Hebbian Principle: Low-Dimensional Structural Projection for Unsupervised Learning


Genesis: Multimodal Driving Scene Generation with Spatio-Temporal and
  Cross-Modal Consistency


Optimal Rates in Continual Linear Regression via Increasing Regularization


FNOPE: Simulation-based inference on function spaces with Fourier Neural Operators


OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domain


Training Language Models to Reason Efficiently


Erasing Conceptual Knowledge from Language Models


SoPo: Text-to-Motion Generation Using Semi-Online Preference Optimization


PartNeXt: A Next-Generation Dataset for Fine-Grained and Hierarchical 3D
  Part Understanding


Perception Encoder: The best visual embeddings are not at the output of the network


CPPO: Accelerating the Training of Group Relative Policy Optimization-Based Reasoning Models


Curvature Tuning: Provable Training-free Model Steering From a Single Parameter


R-KV: Redundancy-aware KV Cache Compression for Training-Free Reasoning Models Acceleration


Analog Foundation Models


Self-supervised Learning of Echocardiographic Video Representations via
  Online Cluster Distillation


REOBench: Benchmarking Robustness of Earth Observation Foundation Models


Uncertainty Estimation on Graphs with Structure Informed Stochastic Partial Differential Equations


Smooth Quadratic Prediction Markets


Text-Aware Real-World Image Super-Resolution via Diffusion Model with Joint Segmentation Decoders


FAME: Adaptive Functional Attention with Expert Routing for
  Function-on-Function Regression


Accurate and Efficient Low-Rank Model Merging in Core Space


EuroSpeech: A Multilingual Speech Corpus


Attention on the Sphere


On Universality Classes of Equivariant Networks


Template-Guided 3D Molecular Pose Generation via Flow Matching and Differentiable Optimization


DPO: A Differential and Pointwise Control Approach to Reinforcement Learning


Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization


Logic.py: Bridging the Gap between LLMs and Constraint Solvers


Recognition through Reasoning: Reinforcing Image Geo-localization with Large Vision-Language Models


PaTH Attention: Position Encoding via Accumulating Householder Transformations


MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?


HermesFlow: Seamlessly Closing the Gap in Multimodal Understanding and Generation


Constant Bit-size Transformers Are Turing Complete


REP: Resource-Efficient Prompting for Rehearsal-Free Continual Learning


$\text{R}^2\text{ec}$: Towards Large Recommender Models with Reasoning


KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills


Normal-Abnormal Guided Generalist Anomaly Detection


FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation


Language Models Can Predict Their Own Behavior


Balanced Token Pruning: Accelerating Vision Language Models Beyond Local
  Optimization


Safety Devolution in AI Agents


Towards Understanding the Mechanisms of Classifier-Free Guidance


BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning   Dataset


QuARI: Query Adaptive Retrieval Improvement


Enhancing Multilingual LLM Pretraining with Model-Based Data Selection


Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving


Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities


C3Po: Cross-View Cross-Modality Correspondence by Pointmap Prediction


On Reasoning Strength Planning in Large Reasoning Models


Simultaneous Swap Regret Minimization via KL-Calibration


Fantastic Bugs and Where to Find Them in AI Benchmarks


Enhancing Safety in Reinforcement Learning with Human Feedback via Rectified Policy Optimization


AVCD: Mitigating Hallucinations in Audio-Visual Large Language Models through Contrastive Decoding


Can We Infer Confidential Properties of Training Data from LLMs?


Web-Shepherd: Advancing PRMs for Reinforcing Web Agents


SOLIDGEO: Measuring Multimodal Spatial Math Reasoning in Solid Geometry


ReservoirTTA: Prolonged Test-time Adaptation for Evolving and Recurring Domains


TwinMarket: A Scalable Behavioral and Social Simulation for Financial   Markets


BridgeVLA: Input-Output Alignment for Efficient 3D Manipulation Learning with Vision-Language Models


Rope to Nope and Back Again: A New Hybrid Attention Strategy


RoboScape: Physics-informed Embodied World Model


Gompertz Linear Units: Leveraging Asymmetry for Enhanced Learning Dynamics


TreeSynth: Synthesizing Diverse Data from Scratch via Tree-Guided Subspace Partitioning


Parameter-free Algorithms for the Stochastically Extended Adversarial Model


Diffusion-Classifier Synergy: Reward-Aligned Learning via Mutual Boosting Loop for FSCIL


GuideFlow3D: Optimization-Guided Rectified Flow For Appearance Transfer


Short-length Adversarial Training Helps LLMs Defend Long-length Jailbreak Attacks: Theoretical and Empirical Evidence


Self-Generated In-Context Examples Improve LLM Agents for Sequential Decision-Making Tasks


Are Large Reasoning Models Good Translation Evaluators? Analysis and
  Performance Boost


Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement


When Do Transformers Outperform Feedforward and Recurrent Networks? A Statistical Perspective


Algorithms and SQ Lower Bounds for Robustly Learning Real-valued Multi-Index Models


The Quest for Universal Master Key Filters in DS-CNNs


GS2E: Gaussian Splatting is an Effective Data Generator for Event Stream Generation


Fairness-aware Bayes Optimal Functional Classification


Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning


SMMILE: An Expert-Driven Benchmark for Multimodal Medical In-Context Learning


Whitened Score Diffusion: A Structured Prior for Imaging Inverse Problems


APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay


System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts


Spiking Meets Attention: Efficient Remote Sensing Image Super-Resolution with Attention Spiking Neural Networks


EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding


The Complexity of Correlated Equilibria in Generalized Games


Multi-View Oriented GPLVM: Expressiveness and Efficiency


Concept-Guided Interpretability via Neural Chunking


Revisiting Multi-Agent World Modeling from a Diffusion-Inspired Perspective


Loquetier: A Virtualized Multi-LoRA Framework for Unified LLM Fine-tuning and Serving


Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification


Non-stationary Bandit Convex Optimization: A Comprehensive Study


Benchmarking Spatiotemporal Reasoning in LLMs and Reasoning Models: Capabilities and Challenges


How do Transformers Learn Implicit Reasoning?


Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits


What Is a Good Caption? A Comprehensive Visual Caption Benchmark for Evaluating Both Correctness and Thoroughness


Bilevel ZOFO: Efficient LLM Fine-Tuning and Meta-Training


Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing


Poison as Cure: Visual Noise for Mitigating Object Hallucinations in LVMs


Regret Analysis of Average-Reward Unichain MDPs via an Actor-Critic Approach


On the rankability of visual embeddings


FAN: Fourier Analysis Networks


Table2LaTeX-RL: High-Fidelity LaTeX Code Generation from Table Images
  via Reinforced Multimodal Language Models


Attention-based clustering


Beyond Accuracy: Dissecting Mathematical Reasoning for LLMs Under Reinforcement Learning


A Partition Cover Approach to Tokenization


Flexible Realignment of Language Models


Document Summarization with Conformal Importance Guarantees


Teaching Language Models to Reason with Tools


RESAnything: Attribute Prompting for Arbitrary Referring Segmentation


Omni-Mol: Exploring Universal Convergent Space for Omni-Molecular Tasks


GLVD: Guided Learned Vertex Descent


NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions


On Transferring Transferability: Towards a Theory for Size Generalization


Token Perturbation Guidance for Diffusion Models


InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy


See through the Dark: Learning Illumination-affined Representations for Nighttime Occupancy Prediction


MetaSlot: Break Through the Fixed Number of Slots in Object-Centric Learning


Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization


MLLMs Need 3D-Aware Representation Supervision for Scene Understanding


Hyperbolic Dataset Distillation


Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning


Efficient Multimodal Dataset Distillation via Generative Models


Text-to-Code Generation for Modular Building Layouts in Building Information Modeling


Guiding Cross-Modal Representations with MLLM Priors via Preference Alignment


Less is More: Local Intrinsic Dimensions of Contextual Language Models


Tree-guided Diffusion Planner


Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts


Evaluating LLM-corrupted Crowdsourcing Data Without Ground Truth


Gated Integration of Low-Rank Adaptation for  Continual Learning of Language Models


RSCC: A Large-Scale Remote Sensing Change Caption Dataset for Disaster
  Events


Universal Few-Shot Spatial Control for Diffusion Models


Learning to Route: Per-Sample Adaptive Routing for Multimodal Multitask Prediction


ADMN: A Layer-Wise Adaptive Multimodal Network for Dynamic Input Noise and Compute Resources


Graph-KV: Breaking Sequence via Injecting Structural Biases into Large
  Language Models


CORE: Reducing UI Exposure in Mobile Agents via Collaboration Between Cloud and Local LLMs


Beyond the Average: Distributional Causal Inference under Imperfect Compliance


On the Expressive Power of Mixture-of-Experts for Structured Complex Tasks


Evolutionary Prediction Games


Instance-Level Composed Image Retrieval


MMTU: A Massive Multi-Task Table Understanding and Reasoning Benchmark


When Semantics Mislead Vision: Mitigating Large Multimodal Models   Hallucinations in Scene Text Spotting and Understanding


MLZero: A Multi-Agent System for End-to-end Machine Learning Automation


Flatten Graphs as Sequences: Transformers are Scalable Graph Generators


MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning


CoreGuard: Safeguarding Foundational Capabilities of LLMs Against Model Stealing in Edge Deployment


Generalized Linear Bandits: Almost Optimal Regret with One-Pass Update


ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training


From Specificity to Generality: Revisiting Generalizable Artifacts in Detecting Face Deepfakes


Reverse Diffusion Sequential Monte Carlo Samplers


Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor


Efficient Multi-modal Large Language Models via Progressive Consistency
  Distillation


Bigram Subnetworks: Mapping to Next Tokens in Transformer Language
  Models


Revisiting Bi-Linear State Transitions in Recurrent Neural Networks


Unified all-atom molecule generation with neural fields


Bifrost-1: Bridging Multimodal LLMs and Diffusion Models with   Patch-level CLIP Latents


RiboFlow: Conditional De Novo RNA Co-Design via Synergistic Flow Matching


Efficient RAW Image Deblurring with Adaptive Frequency Modulation


Direct Alignment with Heterogeneous Preferences


Conformal Risk Training: End-to-end optimization of conformal risk control


Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving


Markov Persuasion Processes: Learning to Persuade From Scratch


Quantum Doubly Stochastic Transformers


Implicit Reward as the Bridge: A Unified View of SFT and DPO Connections


Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Models


Extrapolation by Association: Length Generalization Transfer In Transformers


ChartSketcher: Reasoning with Multimodal Feedback and Reflection for
  Chart Understanding


Let Them Talk: Audio-Driven Multi-Person Conversational Video Generation


CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation


Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs


Composing Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets


Do different prompting methods yield a common task representation in language models?


EraseFlow: Learning Concept Erasure Policies via GFlowNet-Driven Alignment


TREND: Unsupervised 3D Representation Learning via Temporal Forecasting for LiDAR Perception


BraVE: Offline Reinforcement Learning for Discrete Combinatorial Action Spaces


Watermarking Autoregressive Image Generation


Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling


Attack by Yourself: Effective and Unnoticeable Multi-Category Graph Backdoor Attacks with Subgraph Triggers Pool


Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers


Representational Difference Explanations


DiCoFlex: Model-Agnostic Diverse Counterfactuals with Flexible Control


Target Speaker Extraction through Comparing Noisy Positive and Negative Audio Enrollments


Revisiting Residual Connections: Orthogonal Updates for Stable and Efficient Deep Networks


CLIPTTA: Robust Contrastive Vision-Language Test-Time Adaptation


Accelerating Optimization via Differentiable Stopping Time


WebGen-Bench: Evaluating LLMs on Generating Interactive and Functional Websites from Scratch


Unlocking Dataset Distillation with Diffusion Models


Convex Approximation of Two-Layer ReLU Networks for Hidden State Differential Privacy


Shift Before You Learn: Enabling Low-Rank Representations in Reinforcement Learning


Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing


Provable Ordering and Continuity in Vision-Language Pretraining for Generalizable Embodied Agents


Flat Channels to Infinity in Neural Loss Landscapes


Learning long range dependencies through time reversal symmetry breaking


Dynamics-Aligned Latent Imagination in Contextual World Models for Zero-Shot Generalization


Space Group Equivariant Crystal Diffusion


Activation-Informed Merging of Large Language Models


Stratify or Die: Rethinking Data Splits in Image Segmentation


Multi-Class Support Vector Machine with Differential Privacy


Training-Free Guidance Beyond Differentiability: Scalable Path Steering with Tree Search in Diffusion and Flow Models


Bayesian Ego-graph inference for Networked Multi-Agent Reinforcement Learning


Best-of-N Jailbreaking


EAG3R: Event-Augmented 3D Geometry Estimation for Dynamic and Extreme-Lighting Scenes


NeuroGenPoisoning: Neuron-Guided Attacks on Retrieval-Augmented Generation of LLM via Genetic Optimization of External Knowledge


A Regularized Newton Method for Nonconvex Optimization with Global and Local Complexity Guarantees


Risk-aware Direct Preference Optimization under Nested Risk Measure


Reviving DSP for Advanced Theorem Proving in the Era of Reasoning Models


Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation


Embodied Crowd Counting


Hierarchical Implicit Neural Emulators


T2V-OptJail: Discrete Prompt Optimization for Text-to-Video Jailbreak Attacks


Unveiling the Power of Multiple Gossip Steps: A Stability-Based Generalization Analysis in Decentralized Training


On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization


Polyline Path Masked Attention for Vision Transformer


Dataset Distillation of 3D Point Clouds via Distribution Matching


Causal Lifting of Neural Representations: Zero-Shot Generalization for Causal Inferences


Atom of Thoughts for Markov LLM Test-Time Scaling


Self-Adapting Language Models


Variational Learning Finds Flatter Solutions at the Edge of Stability


Seeing is Believing? Mitigating OCR Hallucinations in Multimodal Large Language Models


One Sample is Enough to Make Conformal Prediction Robust


Unlabeled Data Improves Fine-Grained Image Zero-shot Classification with Multimodal LLMs


EffiBench-X: A Multi-Language Benchmark for Measuring Efficiency of
  LLM-Generated Code


SoMi-ToM: Evaluating Multi-Perspective Theory of Mind in Embodied Social
  Interactions


SceneSplat++: A Large Dataset and Comprehensive Benchmark for Language
  Gaussian Splatting


PeRL: Permutation-Enhanced Reinforcement Learning for Interleaved Vision-Language Reasoning


MERIT: Multilingual Semantic Retrieval with Interleaved Multi-Condition Query


MedSG-Bench: A Benchmark for Medical Image Sequences Grounding


Multi-Step Visual Reasoning with Visual Tokens Scaling and Verification


1000+ FPS 4D Gaussian Splatting for Dynamic Scene Rendering


The Narrow Gate: Localized Image-Text Communication in Vision-Language Models


Test-Time Adaptation of Vision-Language Models for Open-Vocabulary Semantic Segmentation


Seeking and Updating with Live Visual Knowledge


Latent Retrieval Augmented Generation of Cross-Domain Protein Binders


ReCon: Region-Controllable Data Augmentation with Rectification and Alignment for Object Detection


CTSketch: Compositional Tensor Sketching for Scalable Neurosymbolic Learning


StelLA: Subspace Learning in Low-rank Adaptation using Stiefel Manifold


Smart Surrogate Losses for Contextual Stochastic Linear Optimization with Robust Constraints


UniEdit: A Unified Knowledge Editing Benchmark for Large Language Models


VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction


Controlling the Flow: Stability and Convergence for Stochastic Gradient Descent with Decaying Regularization


Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation


Mean Flows for One-step Generative Modeling


MiniMax-Remover: Taming Bad Noise Helps Video Object Removal


Fast exact recovery of noisy matrix from few entries: the infinity norm approach


Reconstructing Heterogeneous Biomolecules via Hierarchical Gaussian Mixtures and Part Discovery


AgMMU: A Comprehensive Agricultural Multimodal Understanding and Reasoning Benchmark


Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning


Meta-Learning Objectives for Preference Optimization


Learning in Compact Spaces with Approximately Normalized Transformer


VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video Understanding


Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization


Fundamental Limitations in Defending LLM Finetuning APIs


Mustafar: Promoting Unstructured Sparsity for KV Cache Pruning in LLM Inference


Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning


MuRating: A High Quality Data Selecting Approach to Multilingual Large
  Language Model Pretraining


Visual Anagrams Reveal Hidden Differences in Holistic Shape Processing Across Vision Models


SoFar: Language-Grounded Orientation Bridges Spatial Reasoning and Object Manipulation


Strategic Cost Selection in Participatory Budgeting


Cross-modal Associations in Vision and Language Models: Revisiting the bouba-kiki effect


Improving Generalization of Neural Combinatorial Optimization for Vehicle Routing Problems via Test-Time Projection Learning


Shallow Flow Matching for Coarse-to-Fine Text-to-Speech Synthesis


Reasoning as an Adaptive Defense for Safety


SViMo: Synchronized Diffusion for Video and Motion Generation in Hand-object Interaction Scenarios


Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts


A Graph-Based Synthetic Data Pipeline for Scaling High-Quality Reasoning Instructions


Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability


A Provable Approach for End-to-End Safe Reinforcement Learning


Bridging Sign and Spoken Languages: Pseudo Gloss Generation for Sign Language Translation


One Subgoal at a Time: Zero-Shot Generalization to Arbitrary Linear Temporal Logic Requirements in Multi-Task Reinforcement Learning


Toward Relative Positional Encoding in Spiking Transformers


Characterization and Learning of Causal Graphs from Hard Interventions


IntrinsiX: High-Quality PBR Generation using Image Priors


When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMs


Traversal Verification for Speculative Tree Decoding


Approximation and Generalization Abilities of Score-based Neural Network Generative Models for Sub-Gaussian Distributions


IGD: Token Decisiveness Modeling via Information Gain in LLMs for Personalized Recommendation


The Leaderboard Illusion


3D Visual Illusion Depth Estimation


Controlling Thinking Speed in Reasoning Models


Rethinking Residual Distribution in Locate-then-Edit Model Editing


Graph Diffusion that can Insert and Delete


YOLOv12: Attention-Centric Real-Time Object Detectors


Text-to-Decision Agent: Learning Generalist Policies from Natural Language Supervision


SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution


Panoptic Captioning: Seeking An Equivalency Bridge for Image and Text


Linear Attention for Efficient Bidirectional Sequence Modeling


HopaDIFF: Holistic-Partial Aware Fourier Conditioned Diffusion for Referring Human Action Segmentation in Multi-Person Scenarios


VLMs have Tunnel Vision: Evaluating Nonlocal Visual Reasoning in Leading VLMs


Inpainting the Neural Picture: Inferring Unrecorded Brain Area Dynamics from  Multi-Animal Datasets


Advanced Sign Language Video Generation with Compressed and Quantized
  Multi-Condition Tokenization


Explicitly Modeling Subcortical Vision with a Neuro-Inspired Front-End Improves CNN Robustness


Evolution of Information in Interactive Decision Making:  A Case Study for Multi-Armed Bandits


Cross-Tokenizer Distillation via Approximate Likelihood Matching


A Principled Path to Fitted Distributional Evaluation


Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning


Value-Guided KV Compression for LLMs via Approximated CUR Decomposition


Resource-Constrained Federated Continual Learning: What Does Matter?


Speculative Jacobi-Denoising Decoding for Accelerating Autoregressive
  Text-to-image Generation


Conditional Distribution Compression via the Kernel Conditional Mean Embedding


Jasmine: Harnessing Diffusion Prior for Self-supervised Depth Estimation


Reasoning by Superposition: A Theoretical Perspective on Chain of Continuous Thought


miniF2F-Lean Revisited: Reviewing Limitations and Charting a Path Forward


Chain-of-Model Learning for Language Model


Tight Bounds for Answering Adaptively Chosen Concentrated Queries


RealMath: A Continuous Benchmark for Evaluating Language Models on Research-Level Mathematics


Missing Data Imputation by Reducing Mutual Information with Rectified Flows


Conformal Mixed-Integer Constraint Learning with Feasibility Guarantees


Feedback Guidance of Diffusion Models


RvLLM: LLM Runtime Verification with Domain Knowledge


Constrained Feedback Learning for Non-Stationary Multi-Armed Bandits


CymbaDiff: Structured Spatial Diffusion for Sketch-based 3D Semantic Urban Scene Generation


VidEmo: Affective-Tree Reasoning for Emotion-Centric Video Foundation
  Models


Tracking and Understanding Object Transformations


Individual Regret in Cooperative Stochastic Multi-Armed Bandits


Deep RL Needs Deep Behavior Analysis: Exploring Implicit Planning by Model-Free Agents in Open-Ended Environments


Sampling by averaging: A multiscale approach to score estimation


Breaking the Discretization Barrier of Continuous Physics Simulation Learning


FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities


Instance-Optimality for Private KL Distribution Estimation


DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Driving


ReDi: Rectified Discrete Flow


Uncertainty-Based Smooth Policy Regularisation for Reinforcement Learning with Few Demonstrations


SAGE-Eval: Evaluating LLMs for Systematic Generalizations of Safety
  Facts


Permissioned LLMs: Enforcing Access Control in Large Language Models


BenchmarkCards: Large Language Model and Risk Reporting


Identifiability of Deep Polynomial Neural Networks


Robust Hyperbolic Learning with Curvature-Aware Optimization


Improving Video Generation with Human Feedback


OLA-VLM: Elevating Visual Perception in Multimodal LLMs with Auxiliary Embedding Distillation


UniLumos: Fast and Unified Image and Video Relighting with
  Physics-Plausible Feedback


Factorio Learning Environment


Capturing Individual Human Preferences with Reward Features


How to Learn a Star: Binary Classification with Starshaped Polyhedral Sets


LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders


CURE: Concept Unlearning via Orthogonal Representation Editing in Diffusion Models


A is for Absorption: Studying Feature Splitting and Absorption in Sparse Autoencoders


LinEAS: End-to-end Learning of Activation Steering with a Distributional
  Loss


GeneMAN: Generalizable Single-Image 3D Human Reconstruction from Multi-Source Human Data


On the Integration of Spatial-Temporal Knowledge: A Lightweight Approach to Atmospheric Time Series Forecasting


ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent   Planning


SketchMind:  A Multi-Agent Cognitive Framework for Assessing Student-Drawn Scientific Sketches


Data-Juicer 2.0: Cloud-Scale Adaptive Data Processing for and with Foundation Models


FlowMo: Variance-Based Flow Guidance for Coherent Motion in Video   Generation


TimeZero: Temporal Video Grounding with Reasoning-Guided LVLM


MME-VideoOCR: Evaluating OCR-Based Capabilities of Multimodal LLMs in   Video Scenarios


Capturing Polysemanticity with PRISM: A Multi-Concept Feature
  Description Framework


Flattening Hierarchies with Policy Bootstrapping


BeliefMapNav: 3D Voxel-Based Belief Map for Zero-Shot Object Navigation


Dynamic Rule-Based Defense with Injection Isolation for Securing LLM Agents


Brain-Like Processing Pathways Form in Models With Heterogeneous Experts


Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models


RLZero: Direct Policy Inference from Language Without In-Domain Supervision


Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecasting


A Unified Framework for the Transportability of Population-Level Causal Measures


Actial: Activate Spatial Reasoning Ability of Multimodal Large Language
  Models


When Thinking Drifts: Evidential Grounding for Robust Video Reasoning


UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface


$X^2$-DFD: A framework for eXplainable and eXtendable Deepfake Detection


SHAP zero Explains Biological Sequence Models with Near-zero Marginal Cost for Future Queries


Training Robust Graph Neural Networks by Modeling Noise Dependencies


MIR-Bench: Can Your LLM Recognize Complicated Patterns via Many-Shot In-Context Reasoning?


SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation


STEER-ME: Assessing the Microeconomic Reasoning of Large Language Models


Generalizing while preserving monotonicity in comparison-based preference learning models


SceneForge: Enhancing 3D-text alignment with Structured Scene Compositions


Blockwise Flow Matching: Improving Flow Matching Models For Efficient
  High-Quality Generation


Investigating and Improving Counter-Stereotypical Action Relation in Text-to-Image Diffusion Models


RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human
  Mobility


Polar Sparsity: High Throughput Batched LLM Inferencing with Scalable Contextual Sparsity


Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph


A learnability analysis on neuro-symbolic learning


Towards Implicit Aggregation: Robust Image Representation for Place Recognition in the Transformer Era


DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-Resolution


OSCAR: One-Step Diffusion Codec Across Multiple Bit-rates


ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning


Private Geometric Median in Nearly-Linear Time


Model-Free Graph Data Selection under Distribution Shift


NaViL: Rethinking Scaling Properties of Native Multimodal Large Language
  Models under Data Constraints


Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning


DualOptim: Enhancing Efficacy and Stability in Machine Unlearning with Dual Optimizers


Beyond Token Probes: Hallucination Detection via Activation Tensors with ACT-ViT


Universally Invariant Learning in Equivariant GNNs


YEAST: Yet Another Sequential Test


Differentially Private Relational Learning with Entity-level Privacy Guarantees


ZEUS: Zero-shot Embeddings for Unsupervised Separation of Tabular Data


Distributive Fairness in Large Language Models: Evaluating Alignment with Human Values


Competitive Advantage Attacks to Decentralized Federated Learning


Probably Approximately Precision and Recall Learning