MedConceal: A Benchmark for Clinical Hidden-Concern Reasoning Under Partial Observability

arXiv:2604.08788 · cs.CL · Submitted 2026-04-09 · Read on arXiv

cs.CL

Submitted: 2026-04-09

Updated: 2026-08-28

Terminology

• Benchmark — 53× in this paper · explained in 2 episodes
• Trace — 12× in this paper · explained in 2 episodes
• Actionability — 9× in this paper · explained in 3 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Hysteresis — 2× in this paper · explained in 3 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 4 episodes
• EMMA — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Information Asymmetry — 1× in this paper · explained in 2 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Necessity-Concerns Framework — 1× in this paper
• Progressive Disclosure — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Pseudo-labels — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• MedDialogRubrics: A Comprehensive Benchmark and Evaluation Framework for Multi-turn Medical Consultations in Large Language Models
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Doctor-R1: Mastering Clinical Inquiry with Experiential Agentic Reinforcement Learning
• Communication and Verification in LLM Agents towards Collaboration under Information Asymmetry
• OpenAI GPT-5 System Card

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