Multi-turn evidence seeking reduces LLM diagnostic accuracy by 12.75% and supporting-evidence quality by 24.36% versus full-context evaluation in a new OSCE-inspired benchmark across 468 cases and 15 models.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
STaR-DRO applies momentum-smoothed Tsallis reweighting to focus learning on hard groups in structured prediction, yielding F1 gains on clinical label extraction.
citing papers explorer
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Active Evidence-Seeking and Diagnostic Reasoning in Large Language Models for Clinical Decision Support
Multi-turn evidence seeking reduces LLM diagnostic accuracy by 12.75% and supporting-evidence quality by 24.36% versus full-context evaluation in a new OSCE-inspired benchmark across 468 cases and 15 models.
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STaR-DRO: Stateful Tsallis Reweighting for Group-Robust Structured Prediction
STaR-DRO applies momentum-smoothed Tsallis reweighting to focus learning on hard groups in structured prediction, yielding F1 gains on clinical label extraction.