collaborators

12 papers

cs.AI2026

Agentic Commerce World: An Auditable and Verifiable Environment for Vibe Commerce

Shicheng Fan, Mingdai Yang, Duohao Wang +9

In vibe coding, people describe software in natural language and delegate implementation to AI agents. By analogy, vibe commerce allows people to express buying or selling goals in…

cs.CL2026

ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?

Canyu Chen, Jian Yu, Shan Chen +8

Large Language Models (LLMs) hold great promise to revolutionize current clinical systems for their superior capacities on medical text processing tasks and medical licensing exams…

cs.CY2026

Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges

Baixiang Huang, Canyu Chen, Kai Shu

Accurate attribution of authorship is crucial for maintaining the integrity of digital content, improving forensic investigations, and mitigating the risks of misinformation and pl…

cs.CV2026

Chameleon: Benchmarking Detection and Backtracking on Commercial-Grade AI-Generated Videos

Xingming Liao, Meiyu Zeng, Canyu Chen +3

The proliferation of AI-Generated Content (AIGC), especially deepfake videos, poses a severe threat to social trust by enabling fraud, privacy violations and disinformation. Existi…

cs.RO2026

From Representational Complementarity to Dual Systems: Synergizing VLM and Vision-Only Backbones for End-to-End Driving

Sining Ang, Yuguang Yang, Chenxu Dang +8

Vision-Language-Action (VLA) driving augments end-to-end (E2E) planning with language-enabled visual backbones, yet it remains unclear how vision-language models (VLMs) differ from…

cs.CL2026

Can Editing LLMs Inject Harm?

Canyu Chen, Baixiang Huang, Zekun Li +12

Large Language Models (LLMs) have emerged as a new information channel. Meanwhile, one critical but under-explored question is: Is it possible to bypass the safety alignment and in…