activity
20232026
most citedA Study of Generative Large Language Model for Medical Research and Healthcare

400 citations · 513 across the 22 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CL2024

OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs

Jintian Zhang, Cheng Peng, Mengshu Sun +6

Despite the recent advancements in Large Language Models (LLMs), which have significantly enhanced the generative capabilities for various NLP tasks, LLMs still face limitations in…

cs.CL2024

UF-HOBI at "Discharge Me!": A Hybrid Solution for Discharge Summary Generation Through Prompt-based Tuning of GatorTronGPT Models

Mengxian Lyu, Cheng Peng, Daniel Paredes +4

Automatic generation of discharge summaries presents significant challenges due to the length of clinical documentation, the dispersed nature of patient information, and the divers…

cs.CL2024★ 1 cited

AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation

Wenhao Huang, Zhouhong Gu, Chenghao Peng +5

Web scraping is a powerful technique that extracts data from websites, enabling automated data collection, enhancing data analysis capabilities, and minimizing manual data entry ef…

cs.CL2024★ 1 cited

Improving Generalizability of Extracting Social Determinants of Health Using Large Language Models through Prompt-tuning

Cheng Peng, Zehao Yu, Kaleb E Smith +3

The progress in natural language processing (NLP) using large language models (LLMs) has greatly improved patient information extraction from clinical narratives. However, most met…

cs.CL2024★ 1 cited

Automatic Summarization of Doctor-Patient Encounter Dialogues Using Large Language Model through Prompt Tuning

Mengxian Lyu, Cheng Peng, Xiaohan Li +3

Automatic text summarization (ATS) is an emerging technology to assist clinicians in providing continuous and coordinated care. This study presents an approach to summarize doctor-…

cs.CL2024

NewsBench: A Systematic Evaluation Framework for Assessing Editorial Capabilities of Large Language Models in Chinese Journalism

Miao Li, Ming-Bin Chen, Bo Tang +8

We present NewsBench, a novel evaluation framework to systematically assess the capabilities of Large Language Models (LLMs) for editorial capabilities in Chinese journalism. Our c…

cs.CL2024★ 8 cited

Me LLaMA: Foundation Large Language Models for Medical Applications

Qianqian Xie, Qingyu Chen, Aokun Chen +15

Recent advancements in large language models (LLMs) like ChatGPT and LLaMA show promise in medical applications, yet challenges remain in medical language comprehension. This study…