23 citations · 48 across the 20 of their papers we have counts for
10 papers · 1 filter
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…
Automating Expert-Level Medical Reasoning Evaluation of Large Language Models
Shuang Zhou, Wenya Xie, Jiaxi Li +16
As large language models (LLMs) become increasingly integrated into clinical decision-making, ensuring transparent and trustworthy reasoning is essential. However, existing evaluat…
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…
Retrieval-augmented in-context learning for multimodal large language models in disease classification
Zaifu Zhan, Shuang Zhou, Xiaoshan Zhou +6
Objectives: We aim to dynamically retrieve informative demonstrations, enhancing in-context learning in multimodal large language models (MLLMs) for disease classification. Methods…
EPEE: Towards Efficient and Effective Foundation Models in Biomedicine
Zaifu Zhan, Shuang Zhou, Huixue Zhou +2
Foundation models, including language models, e.g., GPT, and vision models, e.g., CLIP, have significantly advanced numerous biomedical tasks. Despite these advancements, the high…
An evaluation of DeepSeek Models in Biomedical Natural Language Processing
Zaifu Zhan, Shuang Zhou, Huixue Zhou +4
The advancement of Large Language Models (LLMs) has significantly impacted biomedical Natural Language Processing (NLP), enhancing tasks such as named entity recognition, relation…
MMRAG: Multi-Mode Retrieval-Augmented Generation with Large Language Models for Biomedical In-Context Learning
Zaifu Zhan, Jun Wang, Shuang Zhou +2
Objective: To optimize in-context learning in biomedical natural language processing by improving example selection. Methods: We introduce a novel multi-mode retrieval-augmented ge…
PaperHelper: Knowledge-Based LLM QA Paper Reading Assistant
Congrui Yin, Evan Wei, Zhongxing Zhang +1
In the paper, we introduce a paper reading assistant, PaperHelper, a potent tool designed to enhance the capabilities of researchers in efficiently browsing and understanding scien…