SEMJ is a self-evolving multilingual LLM judge that turns cross-lingual inconsistency into iterative self-reflection, outperforming voting and reflection baselines on accuracy and consistency.
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Pith papers citing it
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cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Introduces a French OSCE dialogue dataset of 240 interactions and a modular LLM-based controllable virtual patient generation system with multi-level LLM-as-Judge evaluation for clinical skills training.
citing papers explorer
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When Languages Disagree: Self-Evolving Multilingual LLM Judges
SEMJ is a self-evolving multilingual LLM judge that turns cross-lingual inconsistency into iterative self-reflection, outperforming voting and reflection baselines on accuracy and consistency.
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A French OSCE Dialogue Dataset and Controllable Virtual Patient System for Clinical Training
Introduces a French OSCE dialogue dataset of 240 interactions and a modular LLM-based controllable virtual patient generation system with multi-level LLM-as-Judge evaluation for clinical skills training.