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cs.CL2024
MRAG: A Modular Retrieval Framework for Time-Sensitive Question Answering
Zhang Siyue, Xue Yuxiang, Zhang Yiming +3
Understanding temporal relations and answering time-sensitive questions is crucial yet a challenging task for question-answering systems powered by large language models (LLMs). Ex…
cs.CL2024★ 1 cited
Unlearning Backdoor Attacks for LLMs with Weak-to-Strong Knowledge Distillation
Shuai Zhao, Xiaobao Wu, Cong-Duy Nguyen +4
Parameter-efficient fine-tuning (PEFT) can bridge the gap between large language models (LLMs) and downstream tasks. However, PEFT has been proven vulnerable to malicious attacks.…
cs.CR2024
Breaking PEFT Limitations: Leveraging Weak-to-Strong Knowledge Transfer for Backdoor Attacks in LLMs
Shuai Zhao, Leilei Gan, Zhongliang Guo +5
Despite being widely applied due to their exceptional capabilities, Large Language Models (LLMs) have been proven to be vulnerable to backdoor attacks. These attacks introduce targ…