Examining Reasoning LLMs-as-Judges in Non-Verifiable LLM Post-Training

This research investigates using reasoning Large Language Models (LLMs) as judges for evaluating other LLMs during post-training in non-verifiable domains, exploring their effectiveness, practical impact, and potential pitfalls in complex, subjective tasks.