Xiaogeng Liu

According to our database, Xiaogeng Liu authored at least 16 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding.

Fei Wang, Xingyu Fu, James Y. Huang, Zekun Li, Qin Liu, Xiaogeng Liu, Mingyu Derek Ma, Nan Xu, Wenxuan Zhou, Kai Zhang, Tianyi Lorena Yan, Wenjie Jacky Mo, Hsiang-Hui Liu, Pan Lu, Chunyuan Li, Chaowei Xiao, Kai-Wei Chang, Dan Roth, Sheng Zhang, Hoifung Poon, Muhao Chen

CoRR, 2024

Visual-RolePlay: Universal Jailbreak Attack on MultiModal Large Language Models via Role-playing Image Characte.

Siyuan Ma, Weidi Luo, Yu Wang, Xiaogeng Liu, Muhao Chen, Bo Li, Chaowei Xiao

CoRR, 2024

JailBreakV-28K: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks.

Weidi Luo, Siyuan Ma, Xiaogeng Liu, Xiaoyu Guo, Chaowei Xiao

CoRR, 2024

Don't Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models.

Zhiyuan Yu, Xiaogeng Liu, Shunning Liang, Zach Cameron, Chaowei Xiao, Ning Zhang

CoRR, 2024

AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting.

Yu Wang, Xiaogeng Liu, Yu Li, Muhao Chen, Chaowei Xiao

CoRR, 2024

Automatic and Universal Prompt Injection Attacks against Large Language Models.

Xiaogeng Liu, Zhiyuan Yu, Yizhe Zhang, Ning Zhang, Chaowei Xiao

CoRR, 2024

Don't Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models.

Zhiyuan Yu, Xiaogeng Liu, Shunning Liang, Zach Cameron, Chaowei Xiao, Ning Zhang

Proceedings of the 33rd USENIX Security Symposium, 2024

Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability.

Yechao Zhang, Shengshan Hu, Leo Yu Zhang, Junyu Shi, Minghui Li, Xiaogeng Liu, Wei Wan, Hai Jin

Proceedings of the IEEE Symposium on Security and Privacy, 2024

AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models.

Xiaogeng Liu, Nan Xu, Muhao Chen, Chaowei Xiao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions.

Fangzhou Wu, Xiaogeng Liu, Chaowei Xiao

CoRR, 2023

Why Does Little Robustness Help? Understanding Adversarial Transferability From Surrogate Training.

Yechao Zhang, Shengshan Hu, Leo Yu Zhang, Junyu Shi, Minghui Li, Xiaogeng Liu, Wei Wan, Hai Jin

CoRR, 2023

PointCRT: Detecting Backdoor in 3D Point Cloud via Corruption Robustness.

Shengshan Hu, Wei Liu, Minghui Li, Yechao Zhang, Xiaogeng Liu, Xianlong Wang, Leo Yu Zhang, Junhui Hou

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Detecting Backdoors During the Inference Stage Based on Corruption Robustness Consistency.

Xiaogeng Liu, Minghui Li, Haoyu Wang, Shengshan Hu, Dengpan Ye, Hai Jin, Libing Wu, Chaowei Xiao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Towards Efficient Data-Centric Robust Machine Learning with Noise-based Augmentation.

Xiaogeng Liu, Haoyu Wang, Yechao Zhang, Fangzhou Wu, Shengshan Hu

CoRR, 2022

Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer.

Shengshan Hu, Xiaogeng Liu, Yechao Zhang, Minghui Li, Leo Yu Zhang, Hai Jin, Libing Wu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

AdvHash: Set-to-set Targeted Attack on Deep Hashing with One Single Adversarial Patch.

Shengshan Hu, Yechao Zhang, Xiaogeng Liu, Leo Yu Zhang, Minghui Li, Hai Jin

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021