Jul 2026
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs
This study systematically explores the merging behavior of RL-trained LLMs compared to those trained with traditional SFT, finding that RL significantly reduces task conflicts and results in less performance degradation after merging, making RL-trained models particularly well-suited for this process.
Zi-Xuan Ren, Jinliang Lu, Junhong Wu et al.
· arXiv.org · 3 citations