activity
20242026
collaborators

13 papers

cs.CL2026

Hey, That's My Data! Token-Only Dataset Inference in Large Language Models

Chen Xiong, Zihao Wang, Rui Zhu +4

Large Language Models (LLMs) rely on massive training datasets, often including proprietary data, which raises concerns about unauthorized usage and copyright infringement. Existin…

cs.MA2026

OrgAgent: Organize Your Multi-Agent System like a Company

Yiru Wang, Xinyue Shen, Yaohui Han +3

While large language model-based multi-agent systems have shown strong potential for complex reasoning, how to effectively organize multiple agents remains an open question. In thi…

cs.LG2026

Defining and Evaluating Physical Safety for Large Language Models

Yung-Chen Tang, Pin-Yu Chen, Tsung-Yi Ho

Large Language Models (LLMs) are increasingly used to control robotic systems such as drones, but their risks of causing physical threats and harm in real-world applications remain…

cs.CR2026

Steering Externalities: Benign Activation Steering Unintentionally Increases Jailbreak Risk for Large Language Models

Chen Xiong, Zhiyuan He, Pin-Yu Chen +2

Activation steering is a practical post-training model alignment technique to enhance the utility of Large Language Models (LLMs). Prior to deploying a model as a service, develope…

cs.AI2025

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles

Chen Xiong, Pin-Yu Chen, Tsung-Yi Ho

Recent advances in Large Language Models (LLMs) have spurred transformative applications in various domains, ranging from open-source to proprietary LLMs. However, jailbreak attack…

cs.CR2025

Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs

Xiaomeng Hu, Pin-Yu Chen, Tsung-Yi Ho

As large language models (LLMs) become more integral to society and technology, ensuring their safety becomes essential. Jailbreak attacks exploit vulnerabilities to bypass safety…