3 papers
cs.CL2025
A Simple "Motivation" Can Enhance Reinforcement Finetuning of Large Reasoning Models
Junjie Zhang, Guozheng Ma, Shunyu Liu +6
Reinforcement Learning with Verifiable Rewards~(RLVR) has emerged as a powerful learn-to-reason paradigm for large reasoning models to tackle complex tasks. However, the current RL…
cs.CL2025
Supervised Optimism Correction: Be Confident When LLMs Are Sure
Junjie Zhang, Rushuai Yang, Shunyu Liu +5
In this work, we establish a novel theoretical connection between supervised fine-tuning and offline reinforcement learning under the token-level Markov decision process, revealing…
cs.LG2025
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…