3 citations · 6 across the 8 of their papers we have counts for
7 papers · 1 filter
MedExAgent: Training LLM Agents to Ask, Examine, and Diagnose in Noisy Clinical Environments
Yicheng Gao, Xiaolin Zhou, Yahan Li +2
Real-world clinical diagnosis is a complex process in which the doctor is required to obtain information from both interaction with the patient and conducting medical exams. Additi…
CounselReflect: A Toolkit for Auditing Mental-Health Dialogues
Yahan Li, Chaohao Du, Zeyang Li +5
Mental-health support is increasingly mediated by conversational systems (e.g., LLM-based tools), but users often lack structured ways to audit the quality and potential risks of t…
Beyond Idealized Patients: Evaluating LLMs under Challenging Patient Behaviors in Medical Consultations
Yahan Li, Xinyi Jie, Wanjia Ruan +5
Large language models (LLMs) are increasingly used for medical consultation and health information support. In this high-stakes setting, safety depends not only on medical knowledg…
CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmarking of Large Language Models in Mental Health Question Answering
Yahan Li, Jifan Yao, John Bosco S. Bunyi +3
Medical question answering (QA) benchmarks often focus on multiple-choice or fact-based tasks, leaving open-ended answers to real patient questions underexplored. This gap is parti…
Are Clinical T5 Models Better for Clinical Text?
Yahan Li, Keith Harrigian, Ayah Zirikly +1
Large language models with a transformer-based encoder/decoder architecture, such as T5, have become standard platforms for supervised tasks. To bring these technologies to the cli…
Large Language Model Evaluation via Matrix Nuclear-Norm
Yahan Li, Tingyu Xia, Yi Chang +1
As large language models (LLMs) continue to evolve, efficient evaluation metrics are vital for assessing their ability to compress information and reduce redundancy. While traditio…