4 papers
Though Language Models Err While They Strive: Conformal Prediction for Self-Correcting Scientific Generation
Mingqiao Mo, Yunlong Tan, Hao Zhang
Large language models frequently violate fundamental scientific principles when generating technical content, undermining their reliability in scientific applications. We introduce…
DetectRL-X: Towards Reliable Multilingual and Real-World LLM-Generated Text Detection
Junchao Wu, Yefeng Liu, Chenyu Zhu +8
The effective detection and governance of Large Language Model (LLM) generated content has become increasingly critical due to the growing risk of misuse. Despite the impressive pe…
ShieldedCode: Learning Robust Representations for Virtual Machine Protected Code
Mingqiao Mo, Yunlong Tan, Hao Zhang +2
Large language models (LLMs) have achieved remarkable progress in code generation, yet their potential for software protection remains largely untapped. Reverse engineering continu…
Sugar-Coated Poison: Benign Generation Unlocks LLM Jailbreaking
Yu-Hang Wu, Yu-Jie Xiong, Hao Zhang +2
With the increasingly deep integration of large language models (LLMs) across diverse domains, the effectiveness of their safety mechanisms is encountering severe challenges. Curre…