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20232026
most citedOpenMEDLab: An Open-source Platform for Multi-modality Foundation Models in Medicine

8 citations · 30 across the 34 of their papers we have counts for

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10 papers · 1 filter

cs.CL2026

Human-AI Co-reasoning for Clinical Diagnosis with Evidence-Integrated Language Agent

Zhongzhen Huang, Yan Ling, Hong Chen +7

We present PULSE, a medical reasoning agent that combines a domain-tuned large language model with scientific literature retrieval to support diagnostic decision-making in complex…

cs.CL2026

CURE: A Multimodal Benchmark for Clinical Understanding and Retrieval Evaluation

Yannian Gu, Zhongzhen Huang, Linjie Mu +3

Multimodal large language models (MLLMs) demonstrate considerable potential in clinical diagnostics, a domain that inherently requires synthesizing complex visual and textual data…

cs.CL2025

Elicit and Enhance: Advancing Multimodal Reasoning in Medical Scenarios

Zhongzhen Huang, Linjie Mu, Yakun Zhu +3

Effective clinical decision-making depends on iterative, multimodal reasoning across diverse sources of evidence. The recent emergence of multimodal reasoning models has significan…

cs.CL2025

DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language Models

Yakun Zhu, Zhongzhen Huang, Linjie Mu +6

The emergence of groundbreaking large language models capable of performing complex reasoning tasks holds significant promise for addressing various scientific challenges, includin…

cs.CL2025

O1 Replication Journey -- Part 3: Inference-time Scaling for Medical Reasoning

Zhongzhen Huang, Gui Geng, Shengyi Hua +5

Building upon our previous investigations of O1 replication (Part 1: Journey Learning [Qin et al., 2024] and Part 2: Distillation [Huang et al., 2024]), this work explores the pote…

cs.CL2024★ 2 cited

MedBench: A Comprehensive, Standardized, and Reliable Benchmarking System for Evaluating Chinese Medical Large Language Models

Mianxin Liu, Jinru Ding, Jie Xu +16

Ensuring the general efficacy and goodness for human beings from medical large language models (LLM) before real-world deployment is crucial. However, a widely accepted and accessi…

cs.CL2024

MedOdyssey: A Medical Domain Benchmark for Long Context Evaluation Up to 200K Tokens

Yongqi Fan, Hongli Sun, Kui Xue +3

Numerous advanced Large Language Models (LLMs) now support context lengths up to 128K, and some extend to 200K. Some benchmarks in the generic domain have also followed up on evalu…

cs.CL2024★ 3 cited

Medical Dialogue: A Survey of Categories, Methods, Evaluation and Challenges

Xiaoming Shi, Zeming Liu, Li Du +6

This paper surveys and organizes research works on medical dialog systems, which is an important yet challenging task. Although these systems have been surveyed in the medical comm…

cs.CL2024★ 2 cited

Tool Calling: Enhancing Medication Consultation via Retrieval-Augmented Large Language Models

Zhongzhen Huang, Kui Xue, Yongqi Fan +5

Large-scale language models (LLMs) have achieved remarkable success across various language tasks but suffer from hallucinations and temporal misalignment. To mitigate these shortc…

cs.CL2024★ 2 cited

Evaluating and Enhancing Large Language Models Performance in Domain-specific Medicine: Osteoarthritis Management with DocOA

Xi Chen, MingKe You, Li Wang +7

The efficacy of large language models (LLMs) in domain-specific medicine, particularly for managing complex diseases such as osteoarthritis (OA), remains largely unexplored. This s…