2 papers
cs.LG2026
Behavior Knowledge Merge in Reinforced Agentic Models
Xiangchi Yuan, Dachuan Shi, Chunhui Zhang +4
Reinforcement learning (RL) is central to post-training, particularly for agentic models that require specialized reasoning behaviors. In this setting, model merging offers a pract…
cs.CL2025
Mitigating Forgetting Between Supervised and Reinforcement Learning Yields Stronger Reasoners
Xiangchi Yuan, Xiang Chen, Tong Yu +4
Large Language Models (LLMs) show strong reasoning abilities, often amplified by Chain-of-Thought (CoT) prompting and reinforcement learning (RL). Although RL algorithms can substa…