arXiv (All)
open access
Beyond Idealized Patients: Evaluating LLMs under Challenging Patient Behaviors in Medical Consultations
Large language models (LLMs) are increasingly used for medical consultation and health information support, where safety depends not only on medical knowledge but also on robust responses to unclear, inconsistent, or misleading patient input. However, most existing medical LLM evaluations assume ide
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Learning Personalized Prompts for Healthcare Guidance#798576
- Learning Personalized Prompts for Healthcare Guidance#797163
- ChatGPT v.s. Human in Writing a Preoperative Visit Sheet#1100875
- The Reliability of Human Evaluation of Large Language Models in Health Care Settings: Scoping Review.#653520
- Application of Large Language Models in Emergency Neurology#994871
Record · ID 1156314
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive