collaborators

15 papers

cs.CV2026

Trace, Verify, and Correct: A Training-Free Framework for Spatial Reasoning in Multimodal LLMs

Yang Yang, Jiawei Chen, Tairan Chen +1

Although Multimodal Large Language Models (MLLMs) have made substantial progress, their spatial reasoning may still produce intermediate judgments inconsistent with the input image…

cs.CR2026

VertMark: A Unified Training-Free Robust Watermarking Framework for Vertical Domain Pre-trained Language Models

Cong Kong, Xin Cheng, Zhaoxia Yin +3

With the application of vertical domain pre-trained language models (VPLMs) in specialized fields such as medical, finance, and law, model parameters and inference capabilities hav…

cs.CL2026

Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO

Yu Tian, Jiawei Chen, Lifan Zheng +5

We introduce Skills-Coach, a novel automated framework designed to significantly enhance the self-evolution of skills within Large Language Model (LLM)-based agents. Addressing the…

cs.LG2026

Exploring the Secondary Risks of Large Language Models

Jiawei Chen, Zhengwei Fang, Yu Tian +4

Ensuring the safety and alignment of Large Language Models is a significant challenge with their growing integration into critical applications and societal functions. While prior…

cs.CV2026

Adversarial Attacks on Medical Hyperspectral Imaging Exploiting Spectral-Spatial Dependencies and Multiscale Features

Yunrui Gu, Zhenzhe Gao, Cong Kong +2

Medical hyperspectral imaging (MHSI) has shown strong potential for disease diagnosis by capturing spectral-spatial information of tissues. While deep learning has substantially im…

cs.CR2026

CLASP: Training-Free LLM-Assisted Source Code Watermarking via Semantic-Preserving Transformations

Rui Xu, Jiawei Chen, Weizhi Liu +3

The proliferation of open-source code and large language models (LLMs) for code generation has amplified the risks of unauthorized reuse and intellectual property infringement. Sou…