MedConceal: A Benchmark for Clinical Hidden-Concern Reasoning Under Partial Observability
Patient-clinician communication is an asymmetric-information problem: patients often do not disclose fears, misconceptions, or practical barriers unless clinicians elicit them skillfully. Effective medical dialogue therefore requires reasoning under partial observability: clinicians must elicit latent concerns, confirm them through interaction, and respond in ways that guide patients toward appropriate care. However, existing medical dialogue benchmarks largely sidestep this challenge by exposing hidden patient state, collapsing elicitation into extraction, or evaluating responses without modeling what remains hidden. We present MedConceal, a benchmark with an interactive patient simulato...
| Authors | Yikun Han, Joey Chan, Jingyuan Chen et al. |
|---|---|
| Primary category | cs.CL |
| Published | 9 April 2026 |
| Last updated at source | 28 August 2026 |
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