collaborators

5 papers

cs.CL2026

SSR: Can Simulated Patients Learn to Stigmatize Themselves? Modeling Self-Stigma through Internal Monologue

Kunyao Lan, Bingrui Jin, Zichen Zhu +1

Simulating patients with large language models (LLMs) is a promising tool for mental health training, but existing approaches fail to capture a key clinical reality: self-stigma. P…

cs.CL2026

Synthetic or Authentic? Building Mental Patient Simulators from Longitudinal Evidence

Baihan Li, Bingrui Jin, Kunyao Lan +2

Patient simulation is essential for developing and evaluating mental health dialogue systems. As most existing approaches rely on snapshot-style prompts with limited profile inform…

cs.CY2026

Ethical Risks of Large Language Models in Medical Consultation: An Assessment Based on Reproductive Ethics

Hanhui Xu, Jiacheng Ji, Haoan Jin +2

Background: As large language models (LLMs) are increasingly used in healthcare and medical consultation settings, a growing concern is whether these models can respond to medical…

cs.CL2026

A Human-Centric Pipeline for Aligning Large Language Models with Chinese Medical Ethics

Haoan Jin, Han Ying, Jiacheng Ji +2

Recent advances in large language models have enabled their application to a range of healthcare tasks. However, aligning LLMs with the nuanced demands of medical ethics, especiall…

cs.AI2025

MedKGEval: A Knowledge Graph-Based Multi-Turn Evaluation Framework for Open-Ended Patient Interactions with Clinical LLMs

Yuechun Yu, Han Ying, Haoan Jin +5

The reliable evaluation of large language models (LLMs) in medical applications remains an open challenge, particularly in capturing the complexity of multi-turn doctor-patient int…