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arXiv — cs.AI preprintsInternational19 October 2026

Self- and Other-Labels Induce Bidirectional Bias in LLM Judges

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arXiv:2608.18091v3 Announce Type: replace-cross Abstract: As LLM-as-a-judge becomes increasingly widespread, self-preference -- the tendency of a judge to favor its own outputs -- raises growing concerns about evaluation reliability. However, this bias has been studied predominantly on generated text, where stylistic features and response quality are inevitably conflated. As a result, existing measurements cannot separate genuine self-preference from these confounds. We address this limitation by changing the object of evaluation: instead of judging generated text, ten LLMs assess sets of narr
— arXiv — cs.AI preprints

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