{"total":561,"rows":[{"id":"2602.02214","title":"Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation","created":"2026-02-02","cited_by_count":184,"area":"diffusion"},{"id":"2512.14614","title":"WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling","created":"2025-12-16","cited_by_count":170,"area":"wm"},{"id":"2509.23951","title":"HunyuanImage 3.0 Technical Report","created":"2025-09-28","cited_by_count":149,"area":"moe"},{"id":"2509.24527","title":"Training Agents Inside of Scalable World Models","created":"2025-09-29","cited_by_count":136,"area":"wm"},{"id":"2602.04770","title":"Generative Modeling via Drifting","created":"2026-02-04","cited_by_count":116,"area":null},{"id":"2512.02012","title":"Improved Mean Flows: On the Challenges of Fastforward Generative Models","created":"2025-12-01","cited_by_count":110,"area":null},{"id":"2505.18825","title":"How to build a consistency model: Learning flow maps via self-distillation","created":"2025-05-24","cited_by_count":103,"area":"diffusion"},{"id":"2507.21053","title":"Flow Matching Policy Gradients","created":"2025-07-28","cited_by_count":99,"area":"diffusion"},{"id":"2512.04040","title":"RELIC: Interactive Video World Model with Long-Horizon Memory","created":"2025-12-03","cited_by_count":96,"area":"wm"},{"id":"2506.14603","title":"Align Your Flow: Scaling Continuous-Time Flow Map Distillation","created":"2025-06-17","cited_by_count":87,"area":"diffusion"},{"id":"2510.08431","title":"Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency","created":"2025-10-09","cited_by_count":86,"area":"diffusion"},{"id":"2512.10794","title":"What matters for Representation Alignment: Global Information or Spatial Structure?","created":"2025-12-11","cited_by_count":84,"area":null},{"id":"2512.13507","title":"Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model","created":"2025-12-15","cited_by_count":80,"area":"alignment"},{"id":"2505.14357","title":"Vid2World: Crafting Video Diffusion Models to Interactive World Models","created":"2025-05-20","cited_by_count":76,"area":"wm"},{"id":"2509.15937","title":"A Vision-Language-Action-Critic Model for Robotic Real-World Reinforcement Learning","created":"2025-09-19","cited_by_count":71,"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":"2601.22158","title":"One-step Latent-free Image Generation with Pixel Mean Flows","created":"2026-01-29","cited_by_count":53,"area":null},{"id":"2605.10938","title":"ELF: Embedded Language Flows","created":"2026-05-11","cited_by_count":45,"area":"diffusion"},{"id":"2602.12233","title":"Categorical Flow Maps","created":"2026-02-12","cited_by_count":44,"area":"diffusion"},{"id":"2510.20771","title":"AlphaFlow: Understanding and Improving MeanFlow Models","created":"2025-10-23","cited_by_count":41,"area":"diffusion"},{"id":"2601.14430","title":"Meta Flow Maps enable scalable reward alignment","created":"2026-01-20","cited_by_count":37,"area":null},{"id":"2604.28190","title":"Representation Fr\\'echet Loss for Visual Generation","created":"2026-04-30","cited_by_count":37,"area":null},{"id":"2512.01809","title":"Much Ado About Noising: Dispelling the Myths of Generative Robotic Control","created":"2025-12-01","cited_by_count":36,"area":null},{"id":"2605.10730","title":"Qwen-Image-2.0 Technical Report","created":"2026-05-11","cited_by_count":36,"area":null},{"id":"2509.04394","title":"Transition Models: Rethinking the Generative Learning Objective","created":"2025-09-04","cited_by_count":34,"area":"diffusion"},{"id":"2601.09881","title":"Transition Matching Distillation for Fast Video Generation","created":"2026-01-14","cited_by_count":30,"area":"diffusion"},{"id":"2510.14974","title":"pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation","created":"2025-10-16","cited_by_count":29,"area":null},{"id":"2602.05993","title":"Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps","created":"2026-02-05","cited_by_count":29,"area":"diffusion"},{"id":"2604.09784","title":"Discrete Flow Maps","created":"2026-04-10","cited_by_count":29,"area":null},{"id":"2507.16884","title":"SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling","created":"2025-07-22","cited_by_count":26,"area":"diffusion"},{"id":"2605.13724","title":"AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation","created":"2026-05-13","cited_by_count":26,"area":"diffusion"},{"id":"2507.13231","title":"VITA: Vision-to-Action Flow Matching Policy","created":"2025-07-17","cited_by_count":25,"area":"diffusion"},{"id":"2606.25473","title":"Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models","created":"2026-06-24","cited_by_count":25,"area":"wm"},{"id":"2509.04338","title":"From Editor to Dense Geometry Estimator","created":"2025-09-04","cited_by_count":24,"area":"diffusion"},{"id":"2510.27684","title":"Phased DMD: Few-step Distribution Matching Distillation via Score Matching within Subintervals","created":"2025-10-31","cited_by_count":24,"area":"diffusion"},{"id":"2605.11755","title":"One-Step Generative Modeling via Wasserstein Gradient Flows","created":"2026-05-12","cited_by_count":24,"area":"diffusion"},{"id":"2604.05550","title":"AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model Discovery","created":"2026-04-07","cited_by_count":23,"area":null},{"id":"2507.23675","title":"One-Step Flow Policy Mirror Descent","created":"2025-07-31","cited_by_count":21,"area":"diffusion"},{"id":"2603.19199","title":"FASTER: Rethinking Real-Time Flow VLAs","created":"2026-03-19","cited_by_count":21,"area":"vla"},{"id":"2510.24474","title":"Decoupled MeanFlow: Turning Flow Models into Flow Maps for Accelerated Sampling","created":"2025-10-28","cited_by_count":20,"area":null},{"id":"2511.19797","title":"Terminal Velocity Matching","created":"2025-11-24","cited_by_count":20,"area":"diffusion"},{"id":"2602.03139","title":"Diversity-Preserved Distribution Matching Distillation for Fast Visual Synthesis","created":"2026-02-03","cited_by_count":20,"area":null},{"id":"2509.24526","title":"CMT: Mid-Training for Efficient Learning of Consistency, Mean Flow, and Flow Map Models","created":"2025-09-29","cited_by_count":18,"area":"diffusion"},{"id":"2511.13035","title":"One-Step Generative Policies with Q-Learning: A Reformulation of MeanFlow","created":"2025-11-17","cited_by_count":18,"area":"offlinerl"},{"id":"2512.02636","title":"Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models","created":"2025-12-02","cited_by_count":18,"area":null},{"id":"2512.05150","title":"TwinFlow: Realizing One-step Generation on Large Models with Self-adversarial Flows","created":"2025-12-03","cited_by_count":17,"area":null},{"id":"2509.24335","title":"Hyperspherical Latents Improve Continuous-Token Autoregressive Generation","created":"2025-09-29","cited_by_count":16,"area":"diffusion"},{"id":"2509.25035","title":"Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct","created":"2025-09-29","cited_by_count":16,"area":"diffusion"},{"id":"2511.22688","title":"Test-time scaling of diffusions with flow maps","created":"2025-11-27","cited_by_count":16,"area":"diffusion"},{"id":"2602.07322","title":"Action-to-Action Flow Matching","created":"2026-02-07","cited_by_count":16,"area":"diffusion"},{"id":"2605.28816","title":"Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players","created":"2026-05-27","cited_by_count":15,"area":"wm"},{"id":"2508.06098","title":"MeanAudio: Fast and Faithful Text-to-Audio Generation with Mean Flows","created":"2025-08-08","cited_by_count":14,"area":null},{"id":"2511.19428","title":"Flow Map Distillation Without Data","created":"2025-11-24","cited_by_count":14,"area":null},{"id":"2602.02493","title":"PixelGen: Improving Pixel Diffusion with Perceptual Supervision","created":"2026-02-02","cited_by_count":14,"area":"diffusion"},{"id":"2604.22748","title":"Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond","created":"2026-04-24","cited_by_count":14,"area":"wm"},{"id":"2509.25519","title":"Flow Matching with Semidiscrete Couplings","created":"2025-09-29","cited_by_count":13,"area":"diffusion"},{"id":"2510.14978","title":"Learning an Image Editing Model without Image Editing Pairs","created":"2025-10-16","cited_by_count":13,"area":"diffusion"},{"id":"2512.09914","title":"FALCON: Few-step Accurate Likelihoods for Continuous Flows","created":"2025-12-10","cited_by_count":13,"area":null},{"id":"2512.15657","title":"SoFlow: Solution Flow Models for One-Step Generative Modeling","created":"2025-12-17","cited_by_count":13,"area":"diffusion"},{"id":"2602.20060","title":"MeanFuser: Fast One-Step Multi-Modal Trajectory Generation and Adaptive Reconstruction via MeanFlow for End-to-End Autonomous Driving","created":"2026-02-23","cited_by_count":13,"area":"driving"},{"id":"2604.03118","title":"Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation","created":"2026-04-03","cited_by_count":13,"area":"inference"},{"id":"2510.21608","title":"Generalised Flow Maps for Few-Step Generative Modelling on Riemannian Manifolds","created":"2025-10-24","cited_by_count":12,"area":"diffusion"},{"id":"2511.06055","title":"Neodragon: Mobile Video Generation using Diffusion Transformer","created":"2025-11-08","cited_by_count":12,"area":"diffusion"},{"id":"2511.22475","title":"Adversarial Flow Models","created":"2025-11-27","cited_by_count":12,"area":null},{"id":"2602.05435","title":"Stable Velocity: A Variance Perspective on Flow Matching","created":"2026-02-05","cited_by_count":12,"area":"diffusion"},{"id":"2602.24289","title":"Mode Seeking meets Mean Seeking for Fast Long Video Generation","created":"2026-02-27","cited_by_count":12,"area":"diffusion"},{"id":"2603.16871","title":"WorldCam: Interactive Autoregressive 3D Gaming Worlds with Camera Pose as a Unifying Geometric Representation","created":"2026-03-17","cited_by_count":12,"area":"wm"},{"id":"2508.13904","title":"One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Learning","created":"2025-08-19","cited_by_count":11,"area":"diffusion"},{"id":"2511.21029","title":"FlowerDance: MeanFlow for Efficient and Refined 3D Dance Generation","created":"2025-11-26","cited_by_count":11,"area":null},{"id":"2603.07514","title":"A Unified View of Score-Based and Drifting Models","created":"2026-03-08","cited_by_count":11,"area":"diffusion"},{"id":"2606.24773","title":"Posterior Refinement: Fast Language Generation via Any-Order Flow Maps","created":"2026-06-23","cited_by_count":11,"area":null},{"id":"2607.02375","title":"Representation Distribution Matching for One-Step Visual Generation","created":"2026-07-02","cited_by_count":11,"area":null},{"id":"2505.14502","title":"Learning to Integrate Diffusion ODEs by Averaging the Derivatives","created":"2025-05-20","cited_by_count":10,"area":"diffusion"},{"id":"2508.06082","title":"SwiftVideo: A Unified Framework for Few-Step Video Generation through Trajectory-Distribution Alignment","created":"2025-08-08","cited_by_count":10,"area":null},{"id":"2509.26096","title":"EVODiff: Entropy-aware Variance Optimized Diffusion Inference","created":"2025-09-30","cited_by_count":10,"area":"diffusion"},{"id":"2512.17951","title":"SuperFlow: Training Flow Matching Models with RL on the Fly","created":"2025-12-17","cited_by_count":10,"area":"diffusion"},{"id":"2601.19961","title":"MeanCache: From Instantaneous to Average Velocity for Accelerating Flow Matching Inference","created":"2026-01-27","cited_by_count":10,"area":"diffusion"},{"id":"2602.23901","title":"ABPolicy: Asynchronous B-Spline Flow Policy for Real-Time and Smooth Robotic Manipulation","created":"2026-02-27","cited_by_count":10,"area":null},{"id":"2603.02697","title":"ShareVerse: Multi-Agent Consistent Video Generation for Shared World Modeling","created":"2026-03-03","cited_by_count":10,"area":"wm"},{"id":"2607.26004","title":"Parallel Decoding Distillation for Fast Image and Video Generation","created":"2026-07-28","cited_by_count":10,"area":"diffusion"},{"id":"2507.13343","title":"Taming Diffusion Transformer for Efficient Mobile Video Generation in Seconds","created":"2025-07-17","cited_by_count":9,"area":"diffusion"},{"id":"2602.09024","title":"Autoregressive Image Generation with Masked Bit Modeling","created":"2026-02-09","cited_by_count":9,"area":null},{"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":"2606.18478","title":"Data-Forcing Distillation: Restoring Diversity and Fidelity in Few-Step Video Generation","created":"2026-06-16","cited_by_count":9,"area":"diffusion"},{"id":"2506.01158","title":"Efficient Regression-Based Training of Normalizing Flows for Boltzmann Generators","created":"2025-06-01","cited_by_count":8,"area":"diffusion"},{"id":"2508.06269","title":"OM2P: Offline Multi-Agent Mean-Flow Policy","created":"2025-08-08","cited_by_count":8,"area":"offlinerl"},{"id":"2508.17426","title":"Modular MeanFlow: Towards Stable and Scalable One-Step Generative Modeling","created":"2025-08-24","cited_by_count":8,"area":null},{"id":"2509.25180","title":"DC-Gen: Post-Training Diffusion Acceleration with Deeply Compressed Latent Space","created":"2025-09-29","cited_by_count":8,"area":"diffusion"},{"id":"2510.07865","title":"DM1: MeanFlow with Dispersive Regularization for 1-Step Robotic Manipulation","created":"2025-10-09","cited_by_count":8,"area":null},{"id":"2511.17583","title":"Learning Straight Flows: Variational Flow Matching for Efficient Generation","created":"2025-11-15","cited_by_count":8,"area":"diffusion"},{"id":"2512.02826","title":"From Navigation to Refinement: Revealing the Two-Stage Nature of Flow-based Diffusion Models through Oracle Velocity","created":"2025-12-02","cited_by_count":8,"area":"diffusion"},{"id":"2602.07744","title":"Riemannian MeanFlow","created":"2026-02-08","cited_by_count":8,"area":null},{"id":"2602.13993","title":"Elastic Diffusion Transformer","created":"2026-02-15","cited_by_count":8,"area":"diffusion"},{"id":"2602.15030","title":"Image Generation with a Sphere Encoder","created":"2026-02-16","cited_by_count":8,"area":"diffusion"},{"id":"2602.22654","title":"Denoising as Path Planning: Training-Free Acceleration of Diffusion Models with DPCache","created":"2026-02-26","cited_by_count":8,"area":"diffusion"},{"id":"2603.00976","title":"PreciseCache: Precise Feature Caching for Efficient and High-fidelity Video Generation","created":"2026-03-01","cited_by_count":8,"area":null},{"id":"2605.07820","title":"Scaling Categorical Flow Maps","created":"2026-05-08","cited_by_count":8,"area":"diffusion"},{"id":"2605.13778","title":"Realtime-VLA FLASH: Speculative Inference Framework for Diffusion-based VLAs","created":"2026-05-13","cited_by_count":8,"area":"vla"},{"id":"2605.19771","title":"Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives","created":"2026-05-19","cited_by_count":8,"area":"driving"},{"id":"2509.23122","title":"Stochastic Interpolants via Conditional Dependent Coupling","created":"2025-09-27","cited_by_count":7,"area":null}],"next_cursor":"100"}