5 papers · 1 filter
LLMs for Medical Consultation Are Evaluated Too Late: The Preformulation Gap
Yining Hua, Cyrus Ayubcha, Hongbin Na +4
Large language models for medical consultation are often evaluated after a clinical problem has already been made clear, although real consultations may begin with a vague, minimiz…
CARE-Bench: Benchmarking Patient-Facing LLM Triage
Yining Hua, Hongbin Na, Cyrus Ayubcha
Patient-facing medical LLMs and agents increasingly answer symptom questions before clinician contact, where the key safety question is what action the user should take next. We in…
Designing Benchmarks for Knowledge Work
Yining Hua, Hongbin Na, Cyrus Ayubcha +1
AI agents are moving quickly from answering isolated questions toward completing work through tools, software environments, and multi-step workflows. Much of what these systems are…
MineAgent: Towards Remote-Sensing Mineral Exploration with Multimodal Large Language Models
Beibei Yu, Tao Shen, Hongbin Na +2
Remote-sensing mineral exploration is critical for identifying economically viable mineral deposits, yet it poses significant challenges for multimodal large language models (MLLMs…
Applying and Evaluating Large Language Models in Mental Health Care: A Scoping Review of Human-Assessed Generative Tasks
Yining Hua, Hongbin Na, Zehan Li +4
Large language models (LLMs) are emerging as promising tools for mental health care, offering scalable support through their ability to generate human-like responses. However, the…