3 papers
cs.AI2026
Dense Clinical Contrasts Enhance Medical Knowledge Updating in Large Language Models
Yangmin Huang, Shu Quan, He Geng +5
Medical knowledge changes continually, making large language models vulnerable to relying on outdated yet clinically plausible information. We study whether the format of supervisi…
cs.AI2026
ProMedical: Hierarchical Fine-Grained Criteria Modeling for Medical LLM Alignment via Explicit Injection
He Geng, Yangmin Huang, Lixian Lai +5
Aligning Large Language Models (LLMs) with high-stakes medical standards remains a significant challenge, primarily due to the dissonance between coarse-grained preference signals…
cs.CL2025
MedFact: Benchmarking the Fact-Checking Capabilities of Large Language Models on Chinese Medical Texts
Jiayi He, Yangmin Huang, Qianyun Du +5
Deploying Large Language Models (LLMs) in medical applications requires fact-checking capabilities to ensure patient safety and regulatory compliance. We introduce MedFact, a chall…