15 citations · 29 across the 13 of their papers we have counts for
9 papers · 1 filter
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…
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…
Data Augmentation Techniques for Chinese Disease Name Normalization
Wenqian Cui, Xiangling Fu, Shaohui Liu +4
Disease name normalization is an important task in the medical domain. It classifies disease names written in various formats into standardized names, serving as a fundamental comp…
Reliable and diverse evaluation of LLM medical knowledge mastery
Yuxuan Zhou, Xien Liu, Chen Ning +2
Mastering medical knowledge is crucial for medical-specific LLMs. However, despite the existence of medical benchmarks like MedQA, a unified framework that fully leverages existing…
MultifacetEval: Multifaceted Evaluation to Probe LLMs in Mastering Medical Knowledge
Yuxuan Zhou, Xien Liu, Chen Ning +1
Large language models (LLMs) have excelled across domains, also delivering notable performance on the medical evaluation benchmarks, such as MedQA. However, there still exists a si…
THiFLY Research at SemEval-2023 Task 7: A Multi-granularity System for CTR-based Textual Entailment and Evidence Retrieval
Yuxuan Zhou, Ziyu Jin, Meiwei Li +4
The NLI4CT task aims to entail hypotheses based on Clinical Trial Reports (CTRs) and retrieve the corresponding evidence supporting the justification. This task poses a significant…
Label-guided Learning for Text Classification
Xien Liu, Song Wang, Xiao Zhang +3
Text classification is one of the most important and fundamental tasks in natural language processing. Performance of this task mainly dependents on text representation learning. C…
Tensor Graph Convolutional Networks for Text Classification
Xien Liu, Xinxin You, Xiao Zhang +2
Compared to sequential learning models, graph-based neural networks exhibit some excellent properties, such as ability capturing global information. In this paper, we investigate g…