collaborators

5 papers

cs.CL2025

TCM-Eval: An Expert-Level Dynamic and Extensible Benchmark for Traditional Chinese Medicine

Zihao Cheng, Yuheng Lu, Huaiqian Ye +10

Large Language Models (LLMs) have demonstrated remarkable capabilities in modern medicine, yet their application in Traditional Chinese Medicine (TCM) remains severely limited by t…

cs.CL2025

Learn More, Forget Less: A Gradient-Aware Data Selection Approach for LLM

Yibai Liu, Shihang Wang, Zeming Liu +5

Despite large language models (LLMs) have achieved impressive achievements across numerous tasks, supervised fine-tuning (SFT) remains essential for adapting these models to specia…

cs.SE2025

RepoDebug: Repository-Level Multi-Task and Multi-Language Debugging Evaluation of Large Language Models

Jingjing Liu, Zeming Liu, Zihao Cheng +7

Large Language Models (LLMs) have exhibited significant proficiency in code debugging, especially in automatic program repair, which may substantially reduce the time consumption o…

cs.HC2025

TransBench: Breaking Barriers for Transferable Graphical User Interface Agents in Dynamic Digital Environments

Yuheng Lu, Qian Yu, Hongru Wang +7

Graphical User Interface (GUI) agents, which autonomously operate on digital interfaces through natural language instructions, hold transformative potential for accessibility, auto…

cs.CL2025

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations

Yiming Lei, Zhizheng Yang, Zeming Liu +5

Multi-modal large language models have demonstrated remarkable zero-shot abilities and powerful image-understanding capabilities. However, the existing open-source multi-modal mode…