5 papers
Replay Failures as Successes: Sample-Efficient Reinforcement Learning for Instruction Following
Kongcheng Zhang, Qi Yao, Shunyu Liu +7
Reinforcement Learning (RL) has shown promise for aligning Large Language Models (LLMs) to follow instructions with various constraints. Despite the encouraging results, RL improve…
3MDiT: Unified Tri-Modal Diffusion Transformer for Text-Driven Synchronized Audio-Video Generation
Yaoru Li, Heyu Si, Federico Landi +8
Text-to-video (T2V) diffusion models have recently achieved impressive visual quality, yet most systems still generate silent clips and treat audio as a secondary concern. Existing…
Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning
Kongcheng Zhang, Qi Yao, Shunyu Liu +5
Recent advances of Reinforcement Learning (RL) have highlighted its potential in complex reasoning tasks, yet effective training often relies on external supervision, which limits…
A Survey of Direct Preference Optimization
Shunyu Liu, Wenkai Fang, Zetian Hu +9
Large Language Models (LLMs) have demonstrated unprecedented generative capabilities, yet their alignment with human values remains critical for ensuring helpful and harmless deplo…
Reasoning with Reinforced Functional Token Tuning
Kongcheng Zhang, Qi Yao, Baisheng Lai +5
In this work, we propose Reinforced Functional Token Tuning (RFTT), a novel reinforced fine-tuning framework that empowers Large Language Models (LLMs) with self-play learn-to-reas…