An automated framework using equal-quality response pairs quantifies self-preference bias in LLM judges and reduces it by 31.5% via a cognitive-load-based multi-dimensional evaluation strategy.
36 Notes and Considerations Notes: - Each dimension score must use a 0.25 resolution (e.g., 8.0, 8.25, 8.5, 8.75)
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Quantifying and Mitigating Self-Preference Bias of LLM Judges
An automated framework using equal-quality response pairs quantifies self-preference bias in LLM judges and reduces it by 31.5% via a cognitive-load-based multi-dimensional evaluation strategy.