Research1d ago
vLLM V0 to V1 RL Framework
The vLLM team introduced a new reinforcement learning framework prioritizing correctness before corrections. This approach ensures models master the core logic of a task before refining the output format. It prevents the common pitfall of reward hacking. Practitioners can now train models that prioritize factual accuracy over stylistic mimicry during the RL process.