Performance, Efficiency and Collapse -- Advantages and Challenges in Offline Post-training of Code LLMs

Post-training with reinforcement learning (RL) is a critical phase in the development of code-generating large language models (LLMs), as it ensures adherence to instructions and the production of functionally correct code. This process typically requires computationally intensive code sample genera