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cs.CR2026
UNSEEN: A Cross-Stack LLM Unlearning Defense against AR-LLM Social Engineering Attacks
Tianlong Yu, Yang Yang, Xiao Luo +6
Emerging AR-LLM-based Social Engineering attack (e.g., SEAR) is at the edge of posing great threats to real-world social life. In such AR-LLM-SE attack, the attacker can leverage A…
cs.CR2024★ 3 cited
Generating Is Believing: Membership Inference Attacks against Retrieval-Augmented Generation
Yuying Li, Gaoyang Liu, Chen Wang +1
Retrieval-Augmented Generation (RAG) is a state-of-the-art technique that mitigates issues such as hallucinations and knowledge staleness in Large Language Models (LLMs) by retriev…