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20232026
most citedHealthcare Copilot: Eliciting the Power of General LLMs for Medical Consultation

8 citations · 15 across the 20 of their papers we have counts for

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cs.CL2026

Towards Reliable Medical LLMs: Benchmarking and Enhancing Confidence Estimation of Large Language Models in Medical Consultation

Zhiyao Ren, Yibing Zhan, Siyuan Liang +3

Large-scale language models (LLMs) often offer clinical judgments based on incomplete information, increasing the risk of misdiagnosis. Existing studies have primarily evaluated co…

cs.CL2025

Re-Initialization Token Learning for Tool-Augmented Large Language Models

Chenghao Li, Liu Liu, Baosheng Yu +2

Large language models have demonstrated exceptional performance, yet struggle with complex tasks such as numerical reasoning, plan generation. Integrating external tools, such as c…

cs.CL2024

Towards Training A Chinese Large Language Model for Anesthesiology

Zhonghai Wang, Jie Jiang, Yibing Zhan +8

Medical large language models (LLMs) have gained popularity recently due to their significant practical utility. However, most existing research focuses on general medicine, and th…

cs.CL20248 cited

Healthcare Copilot: Eliciting the Power of General LLMs for Medical Consultation

Zhiyao Ren, Yibing Zhan, Baosheng Yu +2

The copilot framework, which aims to enhance and tailor large language models (LLMs) for specific complex tasks without requiring fine-tuning, is gaining increasing attention from…

cs.CL2024

Large Language Models as an Indirect Reasoner: Contrapositive and Contradiction for Automated Reasoning

Yanfang Zhang, Yiliu Sun, Yibing Zhan +3

Recently, increasing attention has been focused on improving the ability of Large Language Models (LLMs) to perform complex reasoning. Advanced methods, such as Chain-of-Thought (C…