{"total":34,"rows":[{"id":"2501.13918","title":"Improving Video Generation with Human Feedback","created":"2025-01-23","cited_by_count":284,"area":"diffusion"},{"id":"2410.05677","title":"T2V-Turbo-v2: Enhancing Video Generation Model Post-Training through Data, Reward, and Conditional Guidance Design","created":"2024-10-08","cited_by_count":54,"area":"diffusion"},{"id":"2412.15159","title":"OnlineVPO: Align Video Diffusion Model with Online Video-Centric Preference Optimization","created":"2024-12-19","cited_by_count":41,"area":"diffusion"},{"id":"2501.19252","title":"Inference-Time Text-to-Video Alignment with Diffusion Latent Beam Search","created":"2025-01-31","cited_by_count":41,"area":"diffusion"},{"id":"2506.03517","title":"DenseDPO: Fine-Grained Temporal Preference Optimization for Video Diffusion Models","created":"2025-06-04","cited_by_count":34,"area":"diffusion"},{"id":"2412.04462","title":"4Real-Video: Learning Generalizable Photo-Realistic 4D Video Diffusion","created":"2024-12-05","cited_by_count":27,"area":"diffusion"},{"id":"2412.15689","title":"DOLLAR: Few-Step Video Generation via Distillation and Latent Reward Optimization","created":"2024-12-20","cited_by_count":26,"area":"diffusion"},{"id":"2412.15156","title":"Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned LLM","created":"2024-12-19","cited_by_count":25,"area":"diffusion"},{"id":"2505.05474","title":"3D Scene Generation: A Survey","created":"2025-05-08","cited_by_count":24,"area":"diffusion"},{"id":"2502.02088","title":"Dual-IPO: Dual-Iterative Preference Optimization for Text-to-Video Generation","created":"2025-02-04","cited_by_count":13,"area":"diffusion"},{"id":"2601.04153","title":"Diffusion-DRF: Free, Rich, and Differentiable Reward for Video Diffusion Fine-Tuning","created":"2026-01-07","cited_by_count":10,"area":"diffusion"},{"id":"2506.11144","title":"AlignHuman: Improving Motion and Fidelity via Timestep-Segment Preference Optimization for Audio-Driven Human Animation","created":"2025-06-11","cited_by_count":8,"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":"2502.00639","title":"Half-order Fine-Tuning for Diffusion Model: A Recursive Likelihood Ratio Optimizer","created":"2025-02-02","cited_by_count":5,"area":"diffusion"},{"id":"2604.25427","title":"A Systematic Post-Train Framework for Video Generation","created":"2026-04-28","cited_by_count":5,"area":"diffusion"},{"id":"2502.06812","title":"Harness Local Rewards for Global Benefits: Effective Text-to-Video Generation Alignment with Patch-level Reward Models","created":"2025-02-04","cited_by_count":4,"area":"diffusion"},{"id":"2509.26025","title":"PatchVSR: Breaking Video Diffusion Resolution Limits with Patch-wise Video Super-Resolution","created":"2025-09-30","cited_by_count":4,"area":"diffusion"},{"id":"2511.20647","title":"Diverse Video Generation with Determinantal Point Process-Guided Policy Optimization","created":"2025-11-25","cited_by_count":4,"area":"diffusion"},{"id":"2601.04068","title":"Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models","created":"2026-01-07","cited_by_count":4,"area":"diffusion"},{"id":"2511.23146","title":"InstanceV: Instance-Level Video Generation","created":"2025-11-28","cited_by_count":3,"area":"diffusion"},{"id":"2607.23159","title":"CachedSearch: Training-Free Cached Exploration for Test-Time Search in Video Diffusion","created":"2026-07-25","cited_by_count":3,"area":"diffusion"},{"id":"2605.03849","title":"Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation","created":"2026-05-05","cited_by_count":2,"area":"diffusion"},{"id":"2506.10639","title":"GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning","created":"2025-06-12","cited_by_count":1,"area":"diffusion"},{"id":"2508.03254","title":"V.I.P. : Iterative Online Preference Distillation for Efficient Video Diffusion Models","created":"2025-08-05","cited_by_count":1,"area":"diffusion"},{"id":"2510.19193","title":"Video Consistency Distance: Enhancing Temporal Consistency for Image-to-Video Generation via Reward-Based Fine-Tuning","created":"2025-10-22","cited_by_count":1,"area":"diffusion"},{"id":"2603.14294","title":"Seeking Physics in Diffusion Noise","created":"2026-03-15","cited_by_count":1,"area":"diffusion"},{"id":"2605.25661","title":"DRM: Diffusion-based Reward Model With Step-wise Guidance","created":"2026-05-25","cited_by_count":1,"area":"diffusion"},{"id":"2608.13205","title":"HPSD: Hybrid-Policy Self-Distillation for Text-Image-to-Video Diffusion Models","created":"2026-08-13","cited_by_count":1,"area":"diffusion"},{"id":"2608.30194","title":"NoisEasier: Test-Time Noise Optimization for Text-to-Video Generation","created":"2026-08-31","cited_by_count":1,"area":"diffusion"},{"id":"2606.20310","title":"Through the PRISM: Preference Representation in Intermediate States of Video Diffusion Models","created":"2026-06-18","cited_by_count":0,"area":"diffusion"},{"id":"2606.23626","title":"DiT-Reward: Generative Representations for Text-to-Image Reward Modeling","created":"2026-06-22","cited_by_count":0,"area":"diffusion"},{"id":"2607.03960","title":"Reward Lightning: Fast Video Generation via Homologous Preference Distillation","created":"2026-07-04","cited_by_count":0,"area":"diffusion"},{"id":"2608.20011","title":"Manifold Drift in Flow Preference Optimization: A Root Cause of Reward Hacking","created":"2026-08-20","cited_by_count":0,"area":"diffusion"},{"id":"2610.14654","title":"Prospective Forcing: Learning to Look Ahead for Autoregressive Long Video Diffusion","created":"2026-10-10","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}