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20242026
most citedLLMs for Doctors: Leveraging Medical LLMs to Assist Doctors, Not Replace Them

3 citations · 3 across the 6 of their papers we have counts for

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cs.CL2026

Reasoning While Asking: Transforming Reasoning Large Language Models from Passive Solvers to Proactive Inquirers

Xin Chen, Feng Jiang, Yiqian Zhang +5

Reasoning-oriented Large Language Models (LLMs) have achieved remarkable progress with Chain-of-Thought (CoT) prompting, yet they remain fundamentally limited by a \emph{blind self…

cs.CL2025

Enabling Doctor-Centric Medical AI with LLMs through Workflow-Aligned Tasks and Benchmarks

Wenya Xie, Qingying Xiao, Yu Zheng +8

The rise of large language models (LLMs) has transformed healthcare by offering clinical guidance, yet their direct deployment to patients poses safety risks due to limited domain…

cs.CL2025

DPO-Shift: Shifting the Distribution of Direct Preference Optimization

Xiliang Yang, Feng Jiang, Qianen Zhang +2

Direct Preference Optimization (DPO) and its variants have become increasingly popular for aligning language models with human preferences. These methods aim to teach models to bet…

cs.CL20243 cited

LLMs for Doctors: Leveraging Medical LLMs to Assist Doctors, Not Replace Them

Wenya Xie, Qingying Xiao, Yu Zheng +7

The recent success of Large Language Models (LLMs) has had a significant impact on the healthcare field, providing patients with medical advice, diagnostic information, and more. H…

cs.CL2024

: "This is My SQL, Are You With Me?" A Consensus-Based Multi-Agent System for Text-to-SQL Tasks

Hanchen Xia, Feng Jiang, Naihao Deng +4

Large Language Models (LLMs) have demonstrated strong performance on various tasks. To unleash their power on the Text-to-SQL task, we propose (Review-Rebuttal-Revision), a c…

cs.CL2024

Humans or LLMs as the Judge? A Study on Judgement Biases

Guiming Hardy Chen, Shunian Chen, Ziche Liu +2

Adopting human and large language models (LLM) as judges (a.k.a human- and LLM-as-a-judge) for evaluating the performance of LLMs has recently gained attention. Nonetheless, this a…