11 citations · 41 across the 28 of their papers we have counts for
9 papers · 1 filter
Empirical Perturbation Analysis of Linear System Solvers from a Data Poisoning Perspective
Yixin Liu, Arielle Carr, Lichao Sun
The perturbation analysis of linear solvers applied to systems arising broadly in machine learning settings -- for instance, when using linear regression models -- establishes an i…
Can Large Language Models Automatically Jailbreak GPT-4V?
Yuanwei Wu, Yue Huang, Yixin Liu +3
GPT-4V has attracted considerable attention due to its extraordinary capacity for integrating and processing multimodal information. At the same time, its ability of face recogniti…
Virtual Context: Enhancing Jailbreak Attacks with Special Token Injection
Yuqi Zhou, Lin Lu, Hanchi Sun +2
Jailbreak attacks on large language models (LLMs) involve inducing these models to generate harmful content that violates ethics or laws, posing a significant threat to LLM securit…
Self-Cognition in Large Language Models: An Exploratory Study
Dongping Chen, Jiawen Shi, Yao Wan +3
While Large Language Models (LLMs) have achieved remarkable success across various applications, they also raise concerns regarding self-cognition. In this paper, we perform a pion…
GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented Understanding
Dongping Chen, Yue Huang, Siyuan Wu +17
Recently, Multimodal Large Language Models (MLLMs) have been used as agents to control keyboard and mouse inputs by directly perceiving the Graphical User Interface (GUI) and gener…
Physical Backdoor: Towards Temperature-based Backdoor Attacks in the Physical World
Wen Yin, Jian Lou, Pan Zhou +5
Backdoor attacks have been well-studied in visible light object detection (VLOD) in recent years. However, VLOD can not effectively work in dark and temperature-sensitive scenarios…
CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code
Batu Guan, Yao Wan, Zhangqian Bi +4
Large Language Models (LLMs) have achieved remarkable progress in code generation. It now becomes crucial to identify whether the code is AI-generated and to determine the specific…
Does Your Neural Code Completion Model Use My Code? A Membership Inference Approach
Yao Wan, Guanghua Wan, Shijie Zhang +4
Recent years have witnessed significant progress in developing deep learning-based models for automated code completion. Although using source code in GitHub has been a common prac…
Optimization-based Prompt Injection Attack to LLM-as-a-Judge
Jiawen Shi, Zenghui Yuan, Yinuo Liu +4
LLM-as-a-Judge uses a large language model (LLM) to select the best response from a set of candidates for a given question. LLM-as-a-Judge has many applications such as LLM-powered…