Efficient Post-training of LLMs for Code Generation With Offline Reinforcement Learning 事件

Efficient Post-training of LLMs for Code Generation With Offline Reinforcement Learning arXiv:2605.28409v1 Announce Type: new Abstract: Post-training using online reinforcement learning (RL) is an important training step for LLMs, including code-generating models. However, online RL for code generation involves LLM inference and verification of the generated output, which can take considerable time and resources. In this paper, we explore the application of offline RL to code-generating models