1 citations · 2 across the 8 of their papers we have counts for
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Enhancing the Medical Context-Awareness Ability of LLMs via Multifaceted Self-Refinement Learning
Yuxuan Zhou, Yubin Wang, Bin Wang +4
Large language models (LLMs) have shown great promise in the medical domain, achieving strong performance on several benchmarks. However, they continue to underperform in real-worl…
Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving
Yuxuan Zhou, Xien Liu, Chenwei Yan +8
Large language models (LLMs) have demonstrated remarkable performance on various medical benchmarks, but their capabilities across different cognitive levels remain underexplored.…
LLM Sensitivity Evaluation Framework for Clinical Diagnosis
Chenwei Yan, Xiangling Fu, Yuxuan Xiong +4
Large language models (LLMs) have demonstrated impressive performance across various domains. However, for clinical diagnosis, higher expectations are required for LLM's reliabilit…
MIH-TCCT: Mitigating Inconsistent Hallucinations in LLMs via Event-Driven Text-Code Cyclic Training
Xinxin You, Xien Liu, Qixin Sun +7
Recent methodologies utilizing synthetic datasets have aimed to address inconsistent hallucinations in large language models (LLMs); however,these approaches are primarily tailored…
MKE-Coder: Multi-Axial Knowledge with Evidence Verification in ICD Coding for Chinese EMRs
Xinxin You, Xien Liu, Xue Yang +2
The task of automatically coding the International Classification of Diseases (ICD) in the medical field has been well-established and has received much attention. Automatic coding…