5 papers · 1 filter
Principled RL for Flow Matching Emerges from the Chunk-level Policy Optimization
Yifu Luo, Haoyuan Sun, Xinhao Hu +12
Recent Progress in post-training flow matching for text-to-image (T2I) generation with Group Relative Policy Optimization (GRPO) has demonstrated strong potential. However, it is h…
Reinforcement Learning Meets Masked Generative Models: Mask-GRPO for Text-to-Image Generation
Yifu Luo, Xinhao Hu, Keyu Fan +6
Reinforcement learning (RL) has garnered increasing attention in text-to-image (T2I) generation. However, most existing RL approaches are tailored to either diffusion models or aut…
Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning
Kai Qin, Jiaqi Wu, Jianxiang He +8
As Large Language Models (LLMs) demonstrate remarkable capabilities learned from vast corpora, concerns regarding data privacy and safety are receiving increasing attention. LLM un…
The Hidden Link Between RLHF and Contrastive Learning
Xufei Lv, Kehai Chen, Haoyuan Sun +3
Alignment of large language models (LLMs) with human values has recently garnered significant attention, with prominent examples including the canonical yet costly Reinforcement Le…
Reinforcement Fine-Tuning Powers Reasoning Capability of Multimodal Large Language Models
Haoyuan Sun, Jiaqi Wu, Bo Xia +7
Standing in 2025, at a critical juncture in the pursuit of Artificial General Intelligence (AGI), reinforcement fine-tuning (RFT) has demonstrated significant potential in enhancin…