SOURCE-LINKED INTELLIGENCE
JudgeStealer: Extracting LLM Judging Capabilities across Evaluation Protocols
Large language model (LLM) judges are increasingly used across various evaluation scenarios, making their judgment capabilities valuable intellectual property. However, black-box access exposes these capabilities to model extraction attacks. Existing extraction methods do not specifically target LLM judges and provide limited support for multiple evaluation protocols under restricted query budgets. In this study, we propose JUDGESTEALER, the first query-efficient model extraction framework for replicating judging capabilities across pointwise scoring, pairwise comparison, and listwise ranking
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-27T11:28:32.000Z
First collected: 2026-09-21T08:51:59.673Z. This is not the publication date.