Beyond the Surface: Measuring Self-Preference in LLM Judgments (2025.emnlp-main)
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| Challenge: | Existing methods measure self-preference bias by comparing the scores a judge model assigns to its own responses with those assigned to other models. |
| Approach: | They propose to use gold judgments as proxies for the actual quality of responses . they propose to measure self-preference bias as the difference between the judge model's own and other models' scores . |
| Outcome: | The proposed method can assess self-preference bias across large language models . it uses gold judgments as proxies for the ground truth scores of the judge model . |
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