{"total":301,"rows":[{"id":"2510.10274","title":"X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model","created":"2025-10-11","cited_by_count":303,"area":"vla"},{"id":"2502.02538","title":"Flow Q-Learning","created":"2025-02-04","cited_by_count":184,"area":"diffusion"},{"id":"2502.00816","title":"Sundial: A Family of Highly Capable Time Series Foundation Models","created":"2025-02-02","cited_by_count":180,"area":null},{"id":"2506.15799","title":"Steering Your Diffusion Policy with Latent Space Reinforcement Learning","created":"2025-06-18","cited_by_count":169,"area":"diffusion"},{"id":"2507.01925","title":"A Survey on Vision-Language-Action Models: An Action Tokenization Perspective","created":"2025-07-02","cited_by_count":96,"area":"vla"},{"id":"2506.09027","title":"Diffuse and Disperse: Image Generation with Representation Regularization","created":"2025-06-10","cited_by_count":70,"area":"diffusion"},{"id":"2505.23458","title":"Diffusion Guidance Is a Controllable Policy Improvement Operator","created":"2025-05-29","cited_by_count":58,"area":"offlinerl"},{"id":"2506.04168","title":"Horizon Reduction Makes RL Scalable","created":"2025-06-04","cited_by_count":57,"area":"offlinerl"},{"id":"2506.09018","title":"Edit Flows: Flow Matching with Edit Operations","created":"2025-06-10","cited_by_count":55,"area":"diffusion"},{"id":"2503.18886","title":"CFG-Zero*: Improved Classifier-Free Guidance for Flow Matching Models","created":"2025-03-24","cited_by_count":52,"area":"diffusion"},{"id":"2506.03719","title":"On the Closed-Form of Flow Matching: Generalization Does Not Arise from Target Stochasticity","created":"2025-06-04","cited_by_count":50,"area":"diffusion"},{"id":"2502.02150","title":"On the Guidance of Flow Matching","created":"2025-02-04","cited_by_count":45,"area":"diffusion"},{"id":"2510.09459","title":"Failure Prediction at Runtime for Generative Robot Policies","created":"2025-10-10","cited_by_count":42,"area":"diffusion"},{"id":"2503.19385","title":"Inference-Time Scaling for Flow Models via Stochastic Generation and Rollover Budget Forcing","created":"2025-03-25","cited_by_count":38,"area":"lr"},{"id":"2601.14234","title":"Q-learning with Adjoint Matching","created":"2026-01-20","cited_by_count":37,"area":"diffusion"},{"id":"2506.02070","title":"An Introduction to Flow Matching and Diffusion Models","created":"2025-06-02","cited_by_count":35,"area":"diffusion"},{"id":"2602.05993","title":"Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps","created":"2026-02-05","cited_by_count":29,"area":"diffusion"},{"id":"2603.09877","title":"InternVL-U: Democratizing Unified Multimodal Models for Understanding, Reasoning, Generation and Editing","created":"2026-03-10","cited_by_count":28,"area":"lr"},{"id":"2505.22866","title":"Scaling Offline RL via Efficient and Expressive Shortcut Models","created":"2025-05-28","cited_by_count":27,"area":"offlinerl"},{"id":"2503.03206","title":"An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models","created":"2025-03-05","cited_by_count":26,"area":"diffusion"},{"id":"2502.11420","title":"Training-Free Guidance Beyond Differentiability: Scalable Path Steering with Tree Search in Diffusion and Flow Models","created":"2025-02-17","cited_by_count":24,"area":null},{"id":"2503.09817","title":"Temporal Difference Flows","created":"2025-03-12","cited_by_count":24,"area":null},{"id":"2506.17139","title":"Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based Diffusion Models","created":"2025-06-20","cited_by_count":23,"area":"diffusion"},{"id":"2510.11083","title":"Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modeling","created":"2025-10-13","cited_by_count":22,"area":"diffusion"},{"id":"2510.02300","title":"Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models","created":"2025-10-02","cited_by_count":21,"area":null},{"id":"2512.02834","title":"Steering Vision-Language-Action Models as Anti-Exploration: A Test-Time Scaling Approach","created":"2025-12-02","cited_by_count":21,"area":"lr"},{"id":"2603.19199","title":"FASTER: Rethinking Real-Time Flow VLAs","created":"2026-03-19","cited_by_count":21,"area":"vla"},{"id":"2502.09775","title":"CellFlux: Simulating Cellular Morphology Changes via Flow Matching","created":"2025-02-13","cited_by_count":20,"area":"diffusion"},{"id":"2504.18506","title":"Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional","created":"2025-04-25","cited_by_count":20,"area":"diffusion"},{"id":"2509.02055","title":"Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidance","created":"2025-09-02","cited_by_count":20,"area":"vla"},{"id":"2504.10283","title":"$\\alpha$-Flow: A Unified Framework for Continuous-State Discrete Flow Matching Models","created":"2025-04-14","cited_by_count":18,"area":"diffusion"},{"id":"2505.19712","title":"On the Relation between Rectified Flows and Optimal Transport","created":"2025-05-26","cited_by_count":18,"area":"diffusion"},{"id":"2503.10636","title":"The Curse of Conditions: Analyzing and Improving Optimal Transport for Conditional Flow-Based Generation","created":"2025-03-13","cited_by_count":17,"area":"diffusion"},{"id":"2509.20624","title":"FS-DFM: Fast and Accurate Long Text Generation with Few-Step Diffusion Language Models","created":"2025-09-24","cited_by_count":17,"area":"diffusion"},{"id":"2509.25170","title":"GLASS Flows: Transition Sampling for Alignment of Flow and Diffusion Models","created":"2025-09-29","cited_by_count":17,"area":"diffusion"},{"id":"2510.03506","title":"OneFlow: Concurrent Mixed-Modal and Interleaved Generation with Edit Flows","created":"2025-10-03","cited_by_count":17,"area":null},{"id":"2511.22640","title":"Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning","created":"2025-11-27","cited_by_count":17,"area":"diffusion"},{"id":"2512.06112","title":"WAM-Flow: Parallel Coarse-to-Fine Motion Planning via Discrete Flow Matching for Autonomous Driving","created":"2025-12-05","cited_by_count":16,"area":"diffusion"},{"id":"2506.01320","title":"Psi-Sampler: Initial Particle Sampling for SMC-Based Inference-Time Reward Alignment in Score Models","created":"2025-06-02","cited_by_count":15,"area":"diffusion"},{"id":"2510.07650","title":"Value Flows","created":"2025-10-09","cited_by_count":15,"area":"deeprl"},{"id":"2507.17731","title":"Flow Matching Meets Biology and Life Science: A Survey","created":"2025-07-23","cited_by_count":14,"area":"diffusion"},{"id":"2509.22623","title":"A Theoretical Analysis of Discrete Flow Matching Generative Models","created":"2025-09-26","cited_by_count":14,"area":"diffusion"},{"id":"2510.05930","title":"Carr\\'e du champ flow matching: better quality-generalisation tradeoff in generative models","created":"2025-10-07","cited_by_count":14,"area":"diffusion"},{"id":"2504.05400","title":"GARF: Learning Generalizable 3D Reassembly for Real-World Fractures","created":"2025-04-07","cited_by_count":13,"area":null},{"id":"2505.18193","title":"Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry","created":"2025-05-20","cited_by_count":13,"area":"diffusion"},{"id":"2509.25519","title":"Flow Matching with Semidiscrete Couplings","created":"2025-09-29","cited_by_count":13,"area":"diffusion"},{"id":"2512.08108","title":"Scalable Offline Model-Based RL with Action Chunks","created":"2025-12-08","cited_by_count":13,"area":"offlinerl"},{"id":"2510.22512","title":"Transitive RL: Value Learning via Divide and Conquer","created":"2025-10-26","cited_by_count":12,"area":"deeprl"},{"id":"2602.05435","title":"Stable Velocity: A Variance Perspective on Flow Matching","created":"2026-02-05","cited_by_count":12,"area":"diffusion"},{"id":"2605.18678","title":"Lance: Unified Multimodal Modeling by Multi-Task Synergy","created":"2026-05-18","cited_by_count":12,"area":null},{"id":"2506.05526","title":"On Fitting Flow Models with Large Sinkhorn Couplings","created":"2025-06-05","cited_by_count":11,"area":null},{"id":"2602.07132","title":"Discrete Adjoint Matching","created":"2026-02-06","cited_by_count":11,"area":null},{"id":"2511.05005","title":"Multi-agent Coordination via Flow Matching","created":"2025-11-07","cited_by_count":10,"area":"diffusion"},{"id":"2512.23705","title":"Diffusion Knows Transparency: Repurposing Video Diffusion for Transparent Object Depth and Normal Estimation","created":"2025-12-29","cited_by_count":10,"area":"diffusion"},{"id":"2412.11024","title":"Exploring Diffusion and Flow Matching Under Generator Matching","created":"2024-12-15","cited_by_count":9,"area":"diffusion"},{"id":"2503.14494","title":"Deeply Supervised Flow-Based Generative Models","created":"2025-03-18","cited_by_count":9,"area":null},{"id":"2506.08902","title":"Intention-Conditioned Flow Occupancy Models","created":"2025-06-10","cited_by_count":9,"area":null},{"id":"2506.14020","title":"Bures-Wasserstein Flow Matching for Graph Generation","created":"2025-06-16","cited_by_count":9,"area":"diffusion"},{"id":"2506.15864","title":"Improving Rectified Flow with Boundary Conditions","created":"2025-06-18","cited_by_count":9,"area":"diffusion"},{"id":"2509.21906","title":"Error Analysis of Discrete Flow with Generator Matching","created":"2025-09-26","cited_by_count":9,"area":"diffusion"},{"id":"2602.13810","title":"Mean Flow Policy with Instantaneous Velocity Constraint for One-step Action Generation","created":"2026-02-14","cited_by_count":9,"area":"deeprl"},{"id":"2604.27472","title":"PRTS: A Primitive Reasoning and Tasking System via Contrastive Representations","created":"2026-04-30","cited_by_count":9,"area":"vla"},{"id":"2508.06269","title":"OM2P: Offline Multi-Agent Mean-Flow Policy","created":"2025-08-08","cited_by_count":8,"area":"offlinerl"},{"id":"2508.18213","title":"Follow My Hold: Hand-Object Interaction Reconstruction through Geometric Guidance","created":"2025-08-25","cited_by_count":8,"area":"diffusion"},{"id":"2511.17583","title":"Learning Straight Flows: Variational Flow Matching for Efficient Generation","created":"2025-11-15","cited_by_count":8,"area":"diffusion"},{"id":"2602.16796","title":"Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning","created":"2026-02-18","cited_by_count":8,"area":null},{"id":"2503.16973","title":"ARFlow: Human Action-Reaction Flow Matching with Physical Guidance","created":"2025-03-21","cited_by_count":7,"area":"diffusion"},{"id":"2506.20641","title":"Telegrapher's Generative Model via Kac Flows","created":"2025-06-25","cited_by_count":7,"area":"diffusion"},{"id":"2509.03726","title":"Energy-Weighted Flow Matching: Unlocking Continuous Normalizing Flows for Efficient and Scalable Boltzmann Sampling","created":"2025-09-03","cited_by_count":7,"area":"diffusion"},{"id":"2509.23122","title":"Stochastic Interpolants via Conditional Dependent Coupling","created":"2025-09-27","cited_by_count":7,"area":null},{"id":"2509.25157","title":"Chance-constrained Flow Matching for High-Fidelity Constraint-aware Generation","created":"2025-09-29","cited_by_count":7,"area":"diffusion"},{"id":"2512.13255","title":"B\\'ezierFlow: Learning B\\'ezier Stochastic Interpolant Schedulers for Few-Step Generation","created":"2025-12-15","cited_by_count":7,"area":null},{"id":"2602.15984","title":"Verifier-Constrained Flow Expansion for Discovery Beyond the Data","created":"2026-02-17","cited_by_count":7,"area":"diffusion"},{"id":"2506.08894","title":"Product of Experts for Visual Generation","created":"2025-06-10","cited_by_count":6,"area":null},{"id":"2510.08218","title":"Expressive Value Learning for Scalable Offline Reinforcement Learning","created":"2025-10-09","cited_by_count":6,"area":"diffusion"},{"id":"2511.05480","title":"On Flow Matching KL Divergence","created":"2025-11-07","cited_by_count":6,"area":"diffusion"},{"id":"2602.06138","title":"Flow Matching for Offline Reinforcement Learning with Discrete Actions","created":"2026-02-05","cited_by_count":6,"area":"diffusion"},{"id":"2602.11146","title":"Beyond VLM-Based Rewards: Diffusion-Native Latent Reward Modeling","created":"2026-02-11","cited_by_count":6,"area":"diffusion"},{"id":"2603.13300","title":"Safety-Guided Flow (SGF): A Unified Framework for Negative Guidance in Safe Generation","created":"2026-03-02","cited_by_count":6,"area":null},{"id":"2604.15311","title":"LeapAlign: Post-Training Flow Matching Models at Any Generation Step by Building Two-Step Trajectories","created":"2026-04-16","cited_by_count":6,"area":"diffusion"},{"id":"2605.05892","title":"Beyond Steering Vector: Flow-based Activation Steering for Inference-Time Intervention","created":"2026-05-07","cited_by_count":6,"area":"mechinterp"},{"id":"2503.01448","title":"Generative Human Geometry Distribution","created":"2025-03-03","cited_by_count":5,"area":null},{"id":"2505.06549","title":"Good Things Come in Pairs: Paired Autoencoders for Inverse Problems","created":"2025-05-10","cited_by_count":5,"area":null},{"id":"2507.00480","title":"Posterior Inference in Latent Space for Scalable Constrained Black-box Optimization","created":"2025-07-01","cited_by_count":5,"area":null},{"id":"2511.09465","title":"Branching Flows: Discrete, Continuous, and Manifold Flow Matching with Splits and Deletions","created":"2025-11-12","cited_by_count":5,"area":"diffusion"},{"id":"2601.10471","title":"DeFlow: Decoupling Manifold Modeling and Value Maximization for Offline Policy Extraction","created":"2026-01-15","cited_by_count":5,"area":"diffusion"},{"id":"2602.03582","title":"Optimization and Generation in Aerodynamics Inverse Design","created":"2026-02-03","cited_by_count":5,"area":null},{"id":"2603.10718","title":"Riemannian MeanFlow for One-Step Generation on Manifolds","created":"2026-03-11","cited_by_count":5,"area":"diffusion"},{"id":"2605.23993","title":"Nano World Models: A Minimalist Implementation of Future Video Prediction","created":"2026-05-17","cited_by_count":5,"area":"wm"},{"id":"2606.11155","title":"Mean Flow Distillation: Robust and Stable Distillation for Flow Matching Models","created":"2026-06-09","cited_by_count":5,"area":"diffusion"},{"id":"2502.16445","title":"Iterative Flow Matching: Path Correction and Gradual Refinement for Enhanced Generative Modeling","created":"2025-02-23","cited_by_count":4,"area":"diffusion"},{"id":"2504.00494","title":"Flow Matching on Lie Groups","created":"2025-04-01","cited_by_count":4,"area":"diffusion"},{"id":"2504.01338","title":"FlowMotion: Target-Predictive Conditional Flow Matching for Jitter-Reduced Text-Driven Human Motion Generation","created":"2025-04-02","cited_by_count":4,"area":"diffusion"},{"id":"2508.18949","title":"Energy-Based Flow Matching for Generating 3D Molecular Structure","created":"2025-08-26","cited_by_count":4,"area":"diffusion"},{"id":"2510.14981","title":"Coupled Diffusion Sampling for Training-Free Multi-View Image Editing","created":"2025-10-16","cited_by_count":4,"area":"diffusion"},{"id":"2512.11229","title":"REST: Diffusion-based Real-time End-to-end Streaming Talking Head Generation via ID-Context Caching and Asynchronous Streaming Distillation","created":"2025-12-12","cited_by_count":4,"area":"diffusion"},{"id":"2601.13780","title":"Principled Latent Diffusion for Graphs via Laplacian Autoencoders","created":"2026-01-20","cited_by_count":4,"area":"diffusion"},{"id":"2602.05539","title":"Steering Large Reasoning Models towards Concise Reasoning via Flow Matching","created":"2026-02-05","cited_by_count":4,"area":"lr"},{"id":"2602.10326","title":"Flow Matching with Uncertainty Quantification and Guidance","created":"2026-02-10","cited_by_count":4,"area":"diffusion"},{"id":"2602.19980","title":"Discrete Diffusion Models Exploit Asymmetry to Solve Lookahead Planning Tasks","created":"2026-02-23","cited_by_count":4,"area":"diffusion"}],"next_cursor":"100"}