2 papers
cs.CR2026
Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors
Aoying Zheng, Anqi Du, Zizhuang Deng +1
Model quantization is a key technique for reducing storage and inference costs when deploying large language models in practice. However, recent studies show that the discretizatio…
cs.CR2026
FlipGuard: Defending Large Language Models Against Quantization-Conditioned Backdoor Attacks
Aoying Zheng, Anqi Du, Zizhuang Deng +1
Model quantization is essential for the efficient deployment of Large Language Models (LLMs), but introduces a critical vulnerability: Quantization-Conditioned Backdoor (QCB) attac…