{"total":27,"rows":[{"id":"2411.09502","title":"Golden Noise for Diffusion Models: A Learning Framework","created":"2024-11-14","cited_by_count":92,"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":"2410.03190","title":"Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization","created":"2024-10-04","cited_by_count":26,"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":"2411.11727","title":"Aligning Few-Step Diffusion Models with Dense Reward Difference Learning","created":"2024-11-18","cited_by_count":12,"area":"diffusion"},{"id":"2602.05533","title":"Conditional Diffusion Guidance under Hard Constraint: A Stochastic Analysis Approach","created":"2026-02-05","cited_by_count":11,"area":"diffusion"},{"id":"2410.04171","title":"IV-Mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis","created":"2024-10-05","cited_by_count":10,"area":"diffusion"},{"id":"2508.19104","title":"Composition and Alignment of Diffusion Models using Constrained Learning","created":"2025-08-26","cited_by_count":10,"area":"diffusion"},{"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":"2411.10781","title":"Bag of Design Choices for Inference of High-Resolution Masked Generative Transformer","created":"2024-11-16","cited_by_count":7,"area":"diffusion"},{"id":"2412.12594","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","created":"2024-12-17","cited_by_count":7,"area":"diffusion"},{"id":"2505.11070","title":"Towards Self-Improvement of Diffusion Models via Group Preference Optimization","created":"2025-05-16","cited_by_count":7,"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":"2601.15968","title":"HyperAlign: Hypernetwork for Efficient Test-Time Alignment of Diffusion Models","created":"2026-01-22","cited_by_count":4,"area":"diffusion"},{"id":"2602.22570","title":"Guidance Matters: Rethinking the Evaluation Pitfall for Text-to-Image Generation","created":"2026-02-26","cited_by_count":4,"area":"diffusion"},{"id":"2603.18991","title":"CRAFT: Aligning Diffusion Models with Fine-Tuning Is Easier Than You Think","created":"2026-03-19","cited_by_count":4,"area":"diffusion"},{"id":"2411.14871","title":"Preference Alignment for Diffusion Model via Explicit Denoised Distribution Estimation","created":"2024-11-22","cited_by_count":3,"area":"diffusion"},{"id":"2505.17352","title":"Alignment and Safety of Diffusion Models via Reinforcement Learning and Reward Modeling: A Survey","created":"2025-05-23","cited_by_count":3,"area":"diffusion"},{"id":"2506.01511","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","created":"2025-06-02","cited_by_count":3,"area":"diffusion"},{"id":"2605.12112","title":"When Policy Entropy Constraint Fails: Preserving Diversity in Flow-based RLHF via Perceptual Entropy","created":"2026-05-12","cited_by_count":3,"area":"diffusion"},{"id":"2506.00299","title":"Inference-Time Alignment of Diffusion Models via Evolutionary Algorithms","created":"2025-05-30","cited_by_count":2,"area":"diffusion"},{"id":"2510.18851","title":"DP$^2$O-SR: Direct Perceptual Preference Optimization for Real-World Image Super-Resolution","created":"2025-10-21","cited_by_count":2,"area":"diffusion"},{"id":"2605.07456","title":"Inference-Time Attribute Distribution Alignment for Unconditional Diffusion","created":"2026-05-08","cited_by_count":2,"area":"diffusion"},{"id":"2412.12888","title":"ArtAug: Enhancing Text-to-Image Generation through Synthesis-Understanding Interaction","created":"2024-12-17","cited_by_count":1,"area":"diffusion"},{"id":"2510.03089","title":"Latent Diffusion Unlearning: Protecting Against Unauthorized Personalization Through Trajectory Shifted Perturbations","created":"2025-10-03","cited_by_count":1,"area":"diffusion"},{"id":"2503.21812","title":"IPGO: Indirect Prompt Gradient Optimization for Parameter-Efficient Prompt-level Fine-Tuning on Text-to-Image Models","created":"2025-03-25","cited_by_count":0,"area":"diffusion"},{"id":"2605.19532","title":"Boosting Text-to-Image Diffusion Models via Core Token Attention-Based Seed Selection","created":"2026-05-19","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}