{"total":72,"rows":[{"id":"2309.17400","title":"Directly Fine-Tuning Diffusion Models on Differentiable Rewards","created":"2023-09-29","cited_by_count":448,"area":"diffusion"},{"id":"2310.03739","title":"Aligning Text-to-Image Diffusion Models with Reward Backpropagation","created":"2023-10-05","cited_by_count":288,"area":"diffusion"},{"id":"2505.19223","title":"LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models","created":"2025-05-25","cited_by_count":285,"area":"diffusion"},{"id":"2501.13918","title":"Improving Video Generation with Human Feedback","created":"2025-01-23","cited_by_count":284,"area":"diffusion"},{"id":"2408.08252","title":"Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding","created":"2024-08-15","cited_by_count":136,"area":"diffusion"},{"id":"2407.08737","title":"Video Diffusion Alignment via Reward Gradients","created":"2024-07-11","cited_by_count":107,"area":"diffusion"},{"id":"2404.04465","title":"Aligning Diffusion Models by Optimizing Human Utility","created":"2024-04-06","cited_by_count":101,"area":"diffusion"},{"id":"2405.18750","title":"T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback","created":"2024-05-29","cited_by_count":87,"area":"diffusion"},{"id":"2312.12490","title":"InstructVideo: Instructing Video Diffusion Models with Human Feedback","created":"2023-12-19","cited_by_count":86,"area":"diffusion"},{"id":"2401.12244","title":"Large-scale Reinforcement Learning for Diffusion Models","created":"2024-01-20","cited_by_count":78,"area":"diffusion"},{"id":"2509.05952","title":"Coefficients-Preserving Sampling for Reinforcement Learning with Flow Matching","created":"2025-09-07","cited_by_count":56,"area":"diffusion"},{"id":"2402.08265","title":"A Dense Reward View on Aligning Text-to-Image Diffusion with Preference","created":"2024-02-13","cited_by_count":55,"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":"2402.16359","title":"Feedback Efficient Online Fine-Tuning of Diffusion Models","created":"2024-02-26","cited_by_count":53,"area":"diffusion"},{"id":"2402.08714","title":"PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models","created":"2024-02-13","cited_by_count":42,"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":"2503.02039","title":"Dynamic Search for Inference-Time Alignment in Diffusion Models","created":"2025-03-03","cited_by_count":37,"area":"diffusion"},{"id":"2403.11027","title":"Reward Guided Latent Consistency Distillation","created":"2024-03-16","cited_by_count":35,"area":"diffusion"},{"id":"2409.07253","title":"Alignment of Diffusion Models: Fundamentals, Challenges, and Future","created":"2024-09-11","cited_by_count":35,"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":"2410.08134","title":"Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction","created":"2024-10-10","cited_by_count":32,"area":"diffusion"},{"id":"2412.07775","title":"Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets","created":"2024-12-10","cited_by_count":32,"area":"diffusion"},{"id":"2311.15657","title":"Enhancing Diffusion Models with Text-Encoder Reinforcement Learning","created":"2023-11-27","cited_by_count":30,"area":"diffusion"},{"id":"2402.08552","title":"Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases","created":"2024-02-13","cited_by_count":30,"area":"diffusion"},{"id":"2502.13917","title":"TESS 2: A Large-Scale Generalist Diffusion Language Model","created":"2025-02-19","cited_by_count":30,"area":"diffusion"},{"id":"2403.18978","title":"TextCraftor: Your Text Encoder Can be Image Quality Controller","created":"2024-03-27","cited_by_count":27,"area":"diffusion"},{"id":"2412.00759","title":"DyMO: Training-Free Diffusion Model Alignment with Dynamic Multi-Objective Scheduling","created":"2024-12-01","cited_by_count":27,"area":"diffusion"},{"id":"2311.14768","title":"AdaDiff: Adaptive Step Selection for Fast Diffusion Models","created":"2023-11-24","cited_by_count":20,"area":"diffusion"},{"id":"2503.18454","title":"InPO: Inversion Preference Optimization with Reparametrized DDIM for Efficient Diffusion Model Alignment","created":"2025-03-24","cited_by_count":19,"area":"diffusion"},{"id":"2410.12138","title":"Preference Optimization with Multi-Sample Comparisons","created":"2024-10-16","cited_by_count":16,"area":"diffusion"},{"id":"2411.15247","title":"Reward Fine-Tuning Two-Step Diffusion Models via Learning Differentiable Latent-Space Surrogate Reward","created":"2024-11-22","cited_by_count":16,"area":"diffusion"},{"id":"2306.12438","title":"Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback","created":"2023-06-16","cited_by_count":15,"area":"diffusion"},{"id":"2507.15073","title":"Reinforcement Learning for Flow-Matching Policies","created":"2025-07-20","cited_by_count":15,"area":"diffusion"},{"id":"2506.02698","title":"Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences","created":"2025-06-03","cited_by_count":13,"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":"2402.12004","title":"Direct Consistency Optimization for Robust Customization of Text-to-Image Diffusion Models","created":"2024-02-19","cited_by_count":12,"area":"diffusion"},{"id":"2404.04860","title":"ByteEdit: Boost, Comply and Accelerate Generative Image Editing","created":"2024-04-07","cited_by_count":10,"area":"diffusion"},{"id":"2404.05595","title":"UniFL: Improve Latent Diffusion Model via Unified Feedback Learning","created":"2024-04-08","cited_by_count":9,"area":"diffusion"},{"id":"2404.11589","title":"Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding","created":"2024-04-17","cited_by_count":9,"area":"diffusion"},{"id":"2510.08131","title":"Real-Time Motion-Controllable Autoregressive Video Diffusion","created":"2025-10-09","cited_by_count":9,"area":"diffusion"},{"id":"2502.04468","title":"Iterative Importance Fine-tuning of Diffusion Models","created":"2025-02-06","cited_by_count":6,"area":"diffusion"},{"id":"2504.08542","title":"Discriminator-Free Direct Preference Optimization for Video Diffusion","created":"2025-04-11","cited_by_count":6,"area":"diffusion"},{"id":"2410.10166","title":"Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models","created":"2024-10-14","cited_by_count":5,"area":"diffusion"},{"id":"2412.03268","title":"RFSR: Improving ISR Diffusion Models via Reward Feedback Learning","created":"2024-12-04","cited_by_count":5,"area":"diffusion"},{"id":"2507.22604","title":"ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning","created":"2025-07-30","cited_by_count":5,"area":"diffusion"},{"id":"2603.12893","title":"Finite Difference Flow Optimization for RL Post-Training of Text-to-Image Models","created":"2026-03-13","cited_by_count":5,"area":"diffusion"},{"id":"2305.19599","title":"RealignDiff: Boosting Text-to-Image Diffusion Model with Coarse-to-fine Semantic Re-alignment","created":"2023-05-31","cited_by_count":4,"area":"diffusion"},{"id":"2502.12579","title":"CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation","created":"2025-02-18","cited_by_count":4,"area":"diffusion"},{"id":"2509.18928","title":"Direct Preference Optimization for Speech Autoregressive Diffusion Models","created":"2025-09-23","cited_by_count":4,"area":"diffusion"},{"id":"2510.02692","title":"Fine-Tuning Diffusion Models via Intermediate Distribution Shaping","created":"2025-10-03","cited_by_count":4,"area":"diffusion"},{"id":"2510.18072","title":"Fine-tuning Flow Matching Generative Models with Intermediate Feedback","created":"2025-10-20","cited_by_count":4,"area":"diffusion"},{"id":"2601.15968","title":"HyperAlign: Hypernetwork for Efficient Test-Time Alignment of Diffusion Models","created":"2026-01-22","cited_by_count":4,"area":"diffusion"},{"id":"2312.16486","title":"PanGu-Draw: Advancing Resource-Efficient Text-to-Image Synthesis with Time-Decoupled Training and Reusable Coop-Diffusion","created":"2023-12-27","cited_by_count":3,"area":"diffusion"},{"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":"2512.22796","title":"Parallel Diffusion Solver via Residual Dirichlet Policy Optimization","created":"2025-12-28","cited_by_count":3,"area":"diffusion"},{"id":"2509.20570","title":"PIRF: Physics-Informed Reward Fine-Tuning for Diffusion Models","created":"2025-09-24","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":"2601.19232","title":"Structure-based RNA Design by Step-wise Optimization of Latent Diffusion Model","created":"2026-01-27","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":"2603.20828","title":"EruDiff: Refactoring Knowledge in Diffusion Models for Advanced Text-to-Image Synthesis","created":"2026-03-21","cited_by_count":1,"area":"diffusion"},{"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":"2409.11874","title":"ABHINAW: A method for Automatic Evaluation of Typography within AI-Generated Images","created":"2024-09-18","cited_by_count":0,"area":"diffusion"},{"id":"2505.22792","title":"Rhetorical Text-to-Image Generation via Two-layer Diffusion Policy Optimization","created":"2025-05-28","cited_by_count":0,"area":"diffusion"},{"id":"2505.23343","title":"Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering","created":"2025-05-29","cited_by_count":0,"area":"diffusion"},{"id":"2511.20889","title":"Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation","created":"2025-11-25","cited_by_count":0,"area":"diffusion"},{"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":"2603.27599","title":"You Only Erase Once: Erasing Anything without Bringing Unexpected Content","created":"2026-03-29","cited_by_count":0,"area":"diffusion"},{"id":"2607.00486","title":"PAPA: Online Personalized Active Preference Alignment","created":"2026-07-01","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":"2609.06761","title":"LATS: Levy Adaptive Tree Sampling for Feedback-Driven Diverse Target Discovery","created":"2026-09-06","cited_by_count":0,"area":"diffusion"},{"id":"2609.39504","title":"PartiCam: Camera Controlled Video Generation with Reward Guidance","created":"2026-09-30","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}