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Predicting depression severity from AI dialogue can achieve clinical-level accuracy without requiring users to fill out traditional self-report questionnaires.
A round-robin judge assignment strategy, CyclicJudge, precisely eliminates judge bias in LLM evaluation without increasing evaluation costs, offering a practical solution to a pervasive problem.
