4 papers
Resource Consumption Threats in Large Language Models
Yuanhe Zhang, Xinyue Wang, Zhican Chen +8
Given limited and costly computational infrastructure, resource efficiency is a key requirement for large language models (LLMs). Efficient LLMs increase service capacity for provi…
MIDAS: Multi-Image Dispersion and Semantic Reconstruction for Jailbreaking MLLMs
Yilian Liu, Xiaojun Jia, Guoshun Nan +6
Multimodal Large Language Models (MLLMs) have achieved remarkable performance but remain vulnerable to jailbreak attacks that can induce harmful content and undermine their secure…
Auditing Meta-Cognitive Hallucinations in Reasoning Large Language Models
Haolang Lu, Yilian Liu, Jingxin Xu +4
The development of Reasoning Large Language Models (RLLMs) has significantly improved multi-step reasoning capabilities, but it has also made hallucination problems more frequent a…
Two Is Better Than One: Rotations Scale LoRAs
Hongcan Guo, Guoshun Nan, Yuan Yang +9
Scaling Low-Rank Adaptation (LoRA)-based Mixture-of-Experts (MoE) facilitates large language models (LLMs) to efficiently adapt to diverse tasks. However, traditional gating mechan…