activity
20222025
most citedOn the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning

6 citations · 25 across the 31 of their papers we have counts for

collaborators

31 papers

cs.CL20251 cited

DentalBench: Benchmarking and Advancing LLMs Capability for Bilingual Dentistry Understanding

Hengchuan Zhu, Yihuan Xu, Yichen Li +2

Recent advances in large language models (LLMs) and medical LLMs (Med-LLMs) have demonstrated strong performance on general medical benchmarks. However, their capabilities in speci…

cs.CL2025

MedEthicsQA: A Comprehensive Question Answering Benchmark for Medical Ethics Evaluation of LLMs

Jianhui Wei, Zijie Meng, Zikai Xiao +5

While Medical Large Language Models (MedLLMs) have demonstrated remarkable potential in clinical tasks, their ethical safety remains insufficiently explored. This paper introduces…

cs.CV2025

SurgBench: A Unified Large-Scale Benchmark for Surgical Video Analysis

Jianhui Wei, Zikai Xiao, Danyu Sun +4

Surgical video understanding is pivotal for enabling automated intraoperative decision-making, skill assessment, and postoperative quality improvement. However, progress in develop…

cs.CV2025

CAPO: Reinforcing Consistent Reasoning in Medical Decision-Making

Songtao Jiang, Yuan Wang, Ruizhe Chen +8

In medical visual question answering (Med-VQA), achieving accurate responses relies on three critical steps: precise perception of medical imaging data, logical reasoning grounded…

cs.CL2025

Mitigating Posterior Salience Attenuation in Long-Context LLMs with Positional Contrastive Decoding

Zikai Xiao, Ziyang Wang, Wen Ma +5

While Large Language Models (LLMs) support long contexts, they struggle with performance degradation within the context window. Current solutions incur prohibitive training costs,…

cs.CL2025

Fast or Slow? Integrating Fast Intuition and Deliberate Thinking for Enhancing Visual Question Answering

Songtao Jiang, Chenyi Zhou, Yan Zhang +2

Multimodal large language models (MLLMs) still struggle with complex reasoning tasks in Visual Question Answering (VQA). While current methods have advanced by incorporating visual…