preference-evaluation

BAER introduces a backbone-adaptive evidence routing method for robust pairwise LLM judging, achieving higher accuracy across benchmarks by dynamically selecting evidence mechanisms per condition.

CSPF proposes a constrained shared-private fusion method to integrate representations from multiple reward models for non-verifiable preference evaluation, outperforming baselines.