LLMs as Judges: Measuring Bias, Hinting Effects, and Tier Preferences

LLMs used as judges to evaluate other LLMs exhibit measurable self-preference bias, with GPT showing the strongest self-bias and Claude the weakest, while revealing model identities through hinting changes judge behavior unevenly across vendors and domains.