1 citations · 1 across the 5 of their papers we have counts for
8 papers · 1 filter
Can Large Language Models Self-Correct in Medical Question Answering? An Exploratory Study
Zaifu Zhan, Mengyuan Cui, Rui Zhang
Large language models (LLMs) have achieved strong performance on medical question answering (medical QA), and chain-of-thought (CoT) prompting has further improved results by elici…
An Underexplored Frontier: Large Language Models for Rare Disease Patient Education and Communication -- A scoping review
Zaifu Zhan, Yu Hou, Kai Yu +4
Rare diseases affect over 300 million people worldwide and are characterized by complex care pathways, limited clinical expertise, and substantial unmet communication needs through…
Benchmarking GPT-5 for biomedical natural language processing
Yu Hou, Zaifu Zhan, Min Zeng +3
Biomedical literature and clinical narratives pose multifaceted challenges for natural language understanding, from precise entity extraction and document synthesis to multi-step d…
Quantized Large Language Models in Biomedical Natural Language Processing: Evaluation and Recommendation
Zaifu Zhan, Shuang Zhou, Min Zeng +6
Large language models have demonstrated remarkable capabilities in biomedical natural language processing, yet their rapid growth in size and computational requirements present a m…
Data-Efficient Biomedical In-Context Learning: A Diversity-Enhanced Submodular Perspective
Jun Wang, Zaifu Zhan, Qixin Zhang +3
Recent progress in large language models (LLMs) has leveraged their in-context learning (ICL) abilities to enable quick adaptation to unseen biomedical NLP tasks. By incorporating…
Uncertainty-Aware Large Language Models for Explainable Disease Diagnosis
Shuang Zhou, Jiashuo Wang, Zidu Xu +11
Explainable disease diagnosis, which leverages patient information (e.g., signs and symptoms) and computational models to generate probable diagnoses and reasonings, offers clear c…