Author

Ruiyang Qin

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#artificial intelligence Preprint Oct 2026

MOMAT: Mixture of Multiple Atlases for Low-Power Jailbreak Defense of Quantized LLMs

Quantized large language models are increasingly deployed on edge devices for their low latency and energy efficiency. However, model quantization weakens alignment safeguards, leaving qLLMs (quantized large language models) highly vulnerable to jailbreak attacks. To address this challenge, we present MOMAT (Mixture of...

Bo-Yang Li, Bingyu Shen, Wei-Hao Hong et al. · 0 citations

#artificial intelligence Preprint Aug 2026

Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions

Interactions are introduced as a fine-grained tool to analyze prompt sensitivity of LLMs and it is discovered that subtle changes to prompts can trigger severe instability in interactions, even when the outputs of the LLM remain the same.

Ruiyang Qin, Qingzhuo Wang, Tian Wang et al. · 2 citations · ⚡1