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20242026
most citedColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration

26 citations · 44 across the 8 of their papers we have counts for

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Showing cs.CLShow all

5 papers · 1 filter

cs.CL2025★ 1 cited

Auditing medical multi-agent AI reveals risks of false consensus

Yinghao Zhu, Lei Gu, Zixiang Wang +11

Large language models are increasingly being assembled into medical multi-agent systems that emulate multidisciplinary consultation through specialist roles, peer review and consen…

cs.CL2025

Magical: Medical Lay Language Generation via Semantic Invariance and Layperson-tailored Adaptation

Weibin Liao, Tianlong Wang, Yinghao Zhu +3

Medical Lay Language Generation (MLLG) plays a vital role in improving the accessibility of complex scientific content for broader audiences. Recent literature to MLLG commonly emp…

cs.CL2024★ 2 cited

ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Tasks

Yinghao Zhu, Junyi Gao, Zixiang Wang +9

Large Language Models (LLMs) are increasingly deployed in medicine. However, their utility in non-generative clinical prediction, often presumed inferior to specialized models, rem…

cs.CL2024★ 7 cited

Adaptive Activation Steering: A Tuning-Free LLM Truthfulness Improvement Method for Diverse Hallucinations Categories

Tianlong Wang, Xianfeng Jiao, Yinghao Zhu +6

Recent studies have indicated that Large Language Models (LLMs) harbor an inherent understanding of truthfulness, yet often fail to consistently express it and generate false state…

cs.CL2024★ 8 cited

Prompting Large Language Models for Zero-Shot Clinical Prediction with Structured Longitudinal Electronic Health Record Data

Yinghao Zhu, Zixiang Wang, Junyi Gao +6

The inherent complexity of structured longitudinal Electronic Health Records (EHR) data poses a significant challenge when integrated with Large Language Models (LLMs), which are t…