{"total":85,"rows":[{"id":"2505.05470","title":"Flow-GRPO: Training Flow Matching Models via Online RL","created":"2025-05-08","cited_by_count":661,"area":"lr"},{"id":"2501.13918","title":"Improving Video Generation with Human Feedback","created":"2025-01-23","cited_by_count":284,"area":"diffusion"},{"id":"2509.16117","title":"DiffusionNFT: Online Diffusion Reinforcement with Forward Process","created":"2025-09-19","cited_by_count":230,"area":"diffusion"},{"id":"2503.05236","title":"Unified Reward Model for Multimodal Understanding and Generation","created":"2025-03-07","cited_by_count":199,"area":"alignment"},{"id":"2507.21802","title":"MixGRPO: Unlocking Flow-based GRPO Efficiency with Mixed ODE-SDE","created":"2025-07-29","cited_by_count":178,"area":"diffusion"},{"id":"2507.22058","title":"X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again","created":"2025-07-29","cited_by_count":112,"area":"deeprl"},{"id":"2509.06040","title":"BranchGRPO: Stable and Efficient GRPO with Structured Branching in Diffusion Models","created":"2025-09-07","cited_by_count":61,"area":"diffusion"},{"id":"2405.18881","title":"Inference-Time Alignment of Diffusion Models with Direct Noise Optimization","created":"2024-05-29","cited_by_count":55,"area":"diffusion"},{"id":"2502.04194","title":"The Best Instruction-Tuning Data are Those That Fit","created":"2025-02-06","cited_by_count":52,"area":null},{"id":"2404.05600","title":"SpeechAlign: Aligning Speech Generation to Human Preferences","created":"2024-04-08","cited_by_count":47,"area":"alignment"},{"id":"2412.02617","title":"Improving Dynamic Object Interactions in Text-to-Video Generation with AI Feedback","created":"2024-12-03","cited_by_count":47,"area":"mllm"},{"id":"2406.06424","title":"Margin-aware Preference Optimization for Aligning Diffusion Models without Reference","created":"2024-06-10","cited_by_count":46,"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":"2502.02588","title":"Calibrated Multi-Preference Optimization for Aligning Diffusion Models","created":"2025-02-04","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":"2502.01819","title":"Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning","created":"2025-02-03","cited_by_count":33,"area":"diffusion"},{"id":"2507.14119","title":"NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining","created":"2025-07-18","cited_by_count":33,"area":null},{"id":"2506.21656","title":"Fine-Grained Preference Optimization Improves Spatial Reasoning in VLMs","created":"2025-06-26","cited_by_count":32,"area":"lr"},{"id":"2410.03190","title":"Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization","created":"2024-10-04","cited_by_count":26,"area":"diffusion"},{"id":"2502.15588","title":"Improving the Scaling Laws of Synthetic Data with Deliberate Practice","created":"2025-02-21","cited_by_count":17,"area":null},{"id":"2512.24138","title":"GARDO: Reinforcing Diffusion Models without Reward Hacking","created":"2025-12-30","cited_by_count":17,"area":"diffusion"},{"id":"2405.20216","title":"Boost Your Human Image Generation Model via Direct Preference Optimization","created":"2024-05-30","cited_by_count":16,"area":"alignment"},{"id":"2403.06952","title":"SELMA: Learning and Merging Skill-Specific Text-to-Image Experts with Auto-Generated Data","created":"2024-03-11","cited_by_count":14,"area":null},{"id":"2509.25171","title":"TR2-D2: Tree Search Guided Trajectory-Aware Fine-Tuning for Discrete Diffusion","created":"2025-09-29","cited_by_count":14,"area":"diffusion"},{"id":"2603.23500","title":"UniGRPO: Unified Policy Optimization for Reasoning-Driven Visual Generation","created":"2026-03-24","cited_by_count":13,"area":"diffusion"},{"id":"2411.11727","title":"Aligning Few-Step Diffusion Models with Dense Reward Difference Learning","created":"2024-11-18","cited_by_count":12,"area":"diffusion"},{"id":"2511.20256","title":"The Image as Its Own Reward: Reinforcement Learning with Adversarial Reward for Image Generation","created":"2025-11-25","cited_by_count":12,"area":"alignment"},{"id":"2404.04860","title":"ByteEdit: Boost, Comply and Accelerate Generative Image Editing","created":"2024-04-07","cited_by_count":10,"area":"diffusion"},{"id":"2510.14256","title":"Identity-GRPO: Optimizing Multi-Human Identity-preserving Video Generation via Reinforcement Learning","created":"2025-10-16","cited_by_count":10,"area":null},{"id":"2601.05729","title":"TAGRPO: Boosting GRPO on Image-to-Video Generation with Direct Trajectory Alignment","created":"2026-01-09","cited_by_count":10,"area":"lr"},{"id":"2410.05255","title":"Bridging SFT and DPO for Diffusion Model Alignment with Self-Sampling Preference Optimization","created":"2024-10-07","cited_by_count":9,"area":"diffusion"},{"id":"2411.16164","title":"Text-to-Image Synthesis: A Decade Survey","created":"2024-11-25","cited_by_count":9,"area":null},{"id":"2504.10044","title":"Aligning Anime Video Generation with Human Feedback","created":"2025-04-14","cited_by_count":9,"area":"alignment"},{"id":"2510.01549","title":"MIRA: Towards Mitigating Reward Hacking in Inference-Time Alignment of T2I Diffusion Models","created":"2025-10-02","cited_by_count":9,"area":"diffusion"},{"id":"2601.08198","title":"Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs","created":"2026-01-13","cited_by_count":9,"area":"synth"},{"id":"2405.20759","title":"Information Theoretic Text-to-Image Alignment","created":"2024-05-31","cited_by_count":8,"area":"diffusion"},{"id":"2503.10529","title":"PiSA: A Self-Augmented Data Engine and Training Strategy for 3D Understanding with Large Models","created":"2025-03-13","cited_by_count":8,"area":"mllm"},{"id":"2512.04784","title":"PaCo-RL: Advancing Reinforcement Learning for Consistent Image Generation with Pairwise Reward Modeling","created":"2025-12-02","cited_by_count":7,"area":"alignment"},{"id":"2512.07175","title":"SPACE: Noise Contrastive Estimation Stabilizes Self-Play Fine-Tuning for Large Language Models","created":"2025-12-08","cited_by_count":7,"area":"synth"},{"id":"2405.03803","title":"MoDiPO: text-to-motion alignment via AI-feedback-driven Direct Preference Optimization","created":"2024-05-06","cited_by_count":6,"area":"diffusion"},{"id":"2509.22323","title":"RAPID^3: Tri-Level Reinforced Acceleration Policies for Diffusion Transformer","created":"2025-09-26","cited_by_count":6,"area":"diffusion"},{"id":"2512.02793","title":"IC-World: In-Context Generation for Shared World Modeling","created":"2025-12-01","cited_by_count":6,"area":"wm"},{"id":"2512.12387","title":"Anchoring Values in Temporal and Group Dimensions for Flow Matching Model Alignment","created":"2025-12-13","cited_by_count":6,"area":"lr"},{"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":"2605.21573","title":"Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models","created":"2026-05-20","cited_by_count":6,"area":null},{"id":"2412.03268","title":"RFSR: Improving ISR Diffusion Models via Reward Feedback Learning","created":"2024-12-04","cited_by_count":5,"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":"2510.03597","title":"Neon: Negative Extrapolation From Self-Training Improves Image Generation","created":"2025-10-04","cited_by_count":5,"area":null},{"id":"2603.14128","title":"Diffusion Reinforcement Learning via Centered Reward Distillation","created":"2026-03-14","cited_by_count":5,"area":"diffusion"},{"id":"2509.21953","title":"MultiCrafter: High-Fidelity Multi-Subject Generation via Disentangled Attention and Identity-Aware Preference Alignment","created":"2025-09-26","cited_by_count":4,"area":"alignment"},{"id":"2509.25774","title":"PCPO: Proportionate Credit Policy Optimization for Aligning Image Generation Models","created":"2025-09-30","cited_by_count":4,"area":null},{"id":"2504.14534","title":"SUDO: Enhancing Text-to-Image Diffusion Models with Self-Supervised Direct Preference Optimization","created":"2025-04-20","cited_by_count":3,"area":"diffusion"},{"id":"2509.26231","title":"IMG: Calibrating Diffusion Models via Implicit Multimodal Guidance","created":"2025-09-30","cited_by_count":3,"area":"diffusion"},{"id":"2510.18353","title":"Ranking-based Preference Optimization for Diffusion Models from Implicit User Feedback","created":"2025-10-21","cited_by_count":3,"area":"diffusion"},{"id":"2511.05573","title":"Video Text Preservation with Synthetic Text-Rich Videos","created":"2025-11-04","cited_by_count":3,"area":"diffusion"},{"id":"2511.19049","title":"Beyond Reward Margin: Rethinking and Resolving Likelihood Displacement in Diffusion Models via Video Generation","created":"2025-11-24","cited_by_count":3,"area":"diffusion"},{"id":"2605.10937","title":"Power Reinforcement Post-Training of Text-to-Image Models with Super-Linear Advantage Shaping","created":"2026-05-11","cited_by_count":3,"area":"lr"},{"id":"2606.08802","title":"Active Flow Expansion for Out-of-Distribution Discovery: from Theory to Molecules","created":"2026-06-07","cited_by_count":3,"area":null},{"id":"2608.14430","title":"Designing Reinforcement Learning for Diffusion Models: A Unified Path-Space View","created":"2026-08-14","cited_by_count":3,"area":"diffusion"},{"id":"2510.17882","title":"Does GenAI Rewrite How We Write? An Empirical Study on Two-Million Preprints","created":"2025-10-18","cited_by_count":2,"area":null},{"id":"2512.13015","title":"What Happens Next? Next Scene Prediction with a Unified Video Model","created":"2025-12-15","cited_by_count":2,"area":null},{"id":"2512.23426","title":"Direct Diffusion Score Preference Optimization via Stepwise Contrastive Policy-Pair Supervision","created":"2025-12-29","cited_by_count":2,"area":"diffusion"},{"id":"2603.00918","title":"Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards","created":"2026-03-01","cited_by_count":2,"area":"alignment"},{"id":"2605.12179","title":"SyncDPO: Enhancing Temporal Synchronization in Video-Audio Joint Generation via Preference Learning","created":"2026-05-12","cited_by_count":2,"area":"alignment"},{"id":"2605.18365","title":"GeoFlow: Enforcing Implicit Geometric Consistency in Video Generation","created":"2026-05-18","cited_by_count":2,"area":"diffusion"},{"id":"2601.16419","title":"Learning Domain Knowledge in Multimodal Large Language Models through Reinforcement Fine-Tuning","created":"2026-01-23","cited_by_count":1,"area":"mllm"},{"id":"2602.06195","title":"DeDPO: Debiased Direct Preference Optimization for Diffusion Models","created":"2026-02-05","cited_by_count":1,"area":"diffusion"},{"id":"2602.12229","title":"Diffusion Alignment Beyond KL: Variance Minimisation as Effective Policy Optimiser","created":"2026-02-12","cited_by_count":1,"area":"diffusion"},{"id":"2603.01163","title":"BeautyGRPO: Aesthetic Alignment for Face Retouching via Dynamic Path Guidance and Fine-Grained Preference Modeling","created":"2026-03-01","cited_by_count":1,"area":"alignment"},{"id":"2604.22939","title":"Self Knowledge Re-expression: A Fully Local Method for Adapting LLMs to Tasks Using Intrinsic Knowledge","created":"2026-04-24","cited_by_count":1,"area":null},{"id":"2605.09433","title":"Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs","created":"2026-05-10","cited_by_count":1,"area":"diffusion"},{"id":"2606.11075","title":"Exploring the Design Space of Reward Backpropagation for Flow Matching","created":"2026-06-09","cited_by_count":1,"area":"diffusion"},{"id":"2606.15048","title":"Temporal Difference Learning for Diffusion Models","created":"2026-06-13","cited_by_count":1,"area":"diffusion"},{"id":"2606.27147","title":"Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks","created":"2026-06-25","cited_by_count":1,"area":null},{"id":"2607.02291","title":"Optimizing Visual Generative Models via Distribution-wise Rewards","created":"2026-07-02","cited_by_count":1,"area":"alignment"},{"id":"2502.06023","title":"Dual Caption Preference Optimization for Diffusion Models","created":"2025-02-09","cited_by_count":0,"area":"diffusion"},{"id":"2505.21893","title":"SIPO: Stabilized and Improved Preference Optimization for Aligning Diffusion Models","created":"2025-05-28","cited_by_count":0,"area":"diffusion"},{"id":"2506.03621","title":"Negative-Guided Subject Fidelity Optimization for Zero-Shot Subject-Driven Generation","created":"2025-06-04","cited_by_count":0,"area":null},{"id":"2601.21517","title":"HERS: Hidden-Pattern Expert Learning for Risk-Specific Vehicle Damage Adaptation in Diffusion Models","created":"2026-01-29","cited_by_count":0,"area":"diffusion"},{"id":"2604.20933","title":"IRIS: Interpolative R\\'enyi Iterative Self-play for Large Language Model Fine-Tuning","created":"2026-04-22","cited_by_count":0,"area":"synth"},{"id":"2605.04494","title":"Towards General Preference Alignment: Diffusion Models at Nash Equilibrium","created":"2026-05-06","cited_by_count":0,"area":"diffusion"},{"id":"2605.27736","title":"Explicit Critic Guidance for Aligning Diffusion Models","created":"2026-05-26","cited_by_count":0,"area":"diffusion"},{"id":"2607.03770","title":"Self-Improving Diffusion Classifiers with Minority Preference Optimization","created":"2026-07-04","cited_by_count":0,"area":"alignment"},{"id":"2607.06609","title":"D2PO: Optimizing Diffusion Samplers via Dynamic Preference","created":"2026-07-07","cited_by_count":0,"area":"diffusion"},{"id":"2609.35512","title":"Improving Generative Model Self-Training with Geometrically Modified Outputs","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}