Honey I judged the rollouts: How your RL Judge affects your models reasoning — Chinmay Karkar

The author investigates whether using an agentic RL judge to assign credit at the token span level can improve a language model's reasoning and efficiency beyond outcome-only GRPO. Through experiments with the Qwen3.5-4B model on math reasoning datasets, the author finds that while benchmark scores change minimally, judge-guided credit helps the model commit to answers faster and reduces overall token generation. Open article →