3 papers
cs.CL2025
Lifelong Knowledge Editing for Vision Language Models with Low-Rank Mixture-of-Experts
Qizhou Chen, Chengyu Wang, Dakan Wang +3
Model editing aims to correct inaccurate knowledge, update outdated information, and incorporate new data into Large Language Models (LLMs) without the need for retraining. This ta…
cs.CL2024
Imposter.AI: Adversarial Attacks with Hidden Intentions towards Aligned Large Language Models
Xiao Liu, Liangzhi Li, Tong Xiang +4
With the development of large language models (LLMs) like ChatGPT, both their vast applications and potential vulnerabilities have come to the forefront. While developers have inte…
cs.CL2024
Can multiple-choice questions really be useful in detecting the abilities of LLMs?
Wangyue Li, Liangzhi Li, Tong Xiang +3
Multiple-choice questions (MCQs) are widely used in the evaluation of large language models (LLMs) due to their simplicity and efficiency. However, there are concerns about whether…