most citedHuman-Level and Beyond: Benchmarking Large Language Models Against Clinical Pharmacists in Prescription Review

2 citations · 2 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CL2025

MedBench v4: A Robust and Scalable Benchmark for Evaluating Chinese Medical Language Models, Multimodal Models, and Intelligent Agents

Jinru Ding, Lu Lu, Chao Ding +15

Recent advances in medical large language models (LLMs), multimodal models, and agents demand evaluation frameworks that reflect real clinical workflows and safety constraints. We…

cs.CL20252 cited

Human-Level and Beyond: Benchmarking Large Language Models Against Clinical Pharmacists in Prescription Review

Yan Yang, Mouxiao Bian, Peiling Li +10

The rapid advancement of large language models (LLMs) has accelerated their integration into clinical decision support, particularly in prescription review. To enable systematic an…

cs.CL2025

Can Large Language Models Function as Qualified Pediatricians? A Systematic Evaluation in Real-World Clinical Contexts

Siyu Zhu, Mouxiao Bian, Yue Xie +7

With the rapid rise of large language models (LLMs) in medicine, a key question is whether they can function as competent pediatricians in real-world clinical settings. We develope…

cs.CL2025

TCM-5CEval: Extended Deep Evaluation Benchmark for LLM's Comprehensive Clinical Research Competence in Traditional Chinese Medicine

Tianai Huang, Jiayuan Chen, Lu Lu +6

Large language models (LLMs) have demonstrated exceptional capabilities in general domains, yet their application in highly specialized and culturally-rich fields like Traditional…

cs.CL2025

Evaluating the Ability of Large Language Models to Identify Adherence to CONSORT Reporting Guidelines in Randomized Controlled Trials: A Methodological Evaluation Study

Zhichao He, Mouxiao Bian, Jianhong Zhu +7

The Consolidated Standards of Reporting Trials statement is the global benchmark for transparent and high-quality reporting of randomized controlled trials. Manual verification of…

cs.LG2025

Every Attention Matters: An Efficient Hybrid Architecture for Long-Context Reasoning

Ling Team, Bin Han, Caizhi Tang +25

In this technical report, we present the Ring-linear model series, specifically including Ring-mini-linear-2.0 and Ring-flash-linear-2.0. Ring-mini-linear-2.0 comprises 16B paramet…