Who Judges the Judge? Evaluating LLM-as-a-Judge for French Medical open-ended QA
Automatic evaluation of medical open-ended question answering (OEQA) remains challenging due to the need for expert annotations. We evaluate whether large language models (LLMs) can act as judges of semantic equivalence in French medical OEQA, comparing closed-access, general-purpose, and biomedical domain-adapted models. Our results show that LLM-based judgments are strongly influenced by the model that generated the answer, with agreement varying substantially across generators. Domain-adapted and large general-purpose models achieve the highest alignment with expert annotations. We further show that lightweight adaptation of a compact model using supervised fine-tuning (SFT) and Group ...
| Authors | Ikram Belmadani, Oumaima El Khettari, Pacôme Constant dit Beaufils et al. |
|---|---|
| Primary category | cs.CL |
| Published | 4 March 2026 |
| Last updated at source | 4 March 2026 |
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