activity
20242026
most citedAn Agentic System for Rare Disease Diagnosis with Traceable Reasoning

2 citations · 2 across the 5 of their papers we have counts for

collaborators
Showing cs.CLShow all

8 papers · 1 filter

cs.CL20262 cited

An Agentic System for Rare Disease Diagnosis with Traceable Reasoning

Weike Zhao, Chaoyi Wu, Yanjie Fan +10

Rare diseases affect over 300 million individuals worldwide, yet timely and accurate diagnosis remains an urgent challenge. Patients often endure a prolonged diagnostic odyssey exc…

cs.CL2025

MedS: Towards Medical Slow Thinking with Self-Evolved Soft Dual-sided Process Supervision

Shuyang Jiang, Yusheng Liao, Zhe Chen +3

Medical language models face critical barriers to real-world clinical reasoning applications. However, mainstream efforts, which fall short in task coverage, lack fine-grained supe…

cs.CL2025

Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs

Feng Hong, Geng Yu, Yushi Ye +5

Diffusion Large Language Models (DLLMs) have emerged as a compelling alternative to Autoregressive models, designed for fast parallel generation. However, existing DLLMs are plague…

cs.CL2025

AutoMedEval: Harnessing Language Models for Automatic Medical Capability Evaluation

Xiechi Zhang, Zetian Ouyang, Linlin Wang +6

With the proliferation of large language models (LLMs) in the medical domain, there is increasing demand for improved evaluation techniques to assess their capabilities. However, t…

cs.CL2024

TAIA: Large Language Models are Out-of-Distribution Data Learners

Shuyang Jiang, Yusheng Liao, Ya Zhang +2

Fine-tuning on task-specific question-answer pairs is a predominant method for enhancing the performance of instruction-tuned large language models (LLMs) on downstream tasks. Howe…

cs.CL2024

CliMedBench: A Large-Scale Chinese Benchmark for Evaluating Medical Large Language Models in Clinical Scenarios

Zetian Ouyang, Yishuai Qiu, Linlin Wang +4

With the proliferation of Large Language Models (LLMs) in diverse domains, there is a particular need for unified evaluation standards in clinical medical scenarios, where models n…