KlinikeBench: Evaluating Language Models Beyond Diagnostic Accuracy
Most clinical benchmarks evaluate language models (LMs) on diagnosis using complete case descriptions. In clinical practice, however, patients present information in different ways, and clinicians must obtain relevant history and determine which examinations are needed before reaching a diagnosis. Diagnostic accuracy alone therefore cannot establish whether an agent gathered essential information or conducted an appropriate clinical assessment. Furthermore, existing benchmarks lack professional clinicians' verification. To address this gap, we introduce KlinikeBench, a benchmark of 333 clinician-authored tasks, each providing an isolated sandbox environment with a virtual patient, clinica...
| Authors | Xueting Fang, Zehui Li, Yang Yang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 29 September 2026 |
| Last updated at source | 6 October 2026 |
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- anon-caa-neurips/klinikebenchDataset · cited by
- anon-caa-neurips/KLINIKEBENCH-TrajectoriesDataset · cited by
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