Zihao Zhu

@article{zhu2025bot,
  title = {BoT: Breaking Long Thought Processes of o1-like Large Language Models through Backdoor Attack},
  author = {Zhu, Zihao and Zhang, Hongbao and Zhang, Mingda and Wang, Ruotong and Wu, Guanzong and Ke, Xu and Wu, Baoyuan},
  journal = {arXiv preprint},
  year = {2025},
}

@article{zhu2024hmgie,
  title = {HMGIE: Hierarchical and Multi-Grained Inconsistency Evaluation for Vision-Language Data Cleansing},
  author = {Zhu, Zihao and Zhang, Hongbao and Wu, Guanzong and Lyu, Siwei and Wu, Baoyuan},
  journal = {arXiv preprint},
  year = {2024},
}

@article{zhang2024reliable,
  title = {Reliable Poisoned Sample Detection against Backdoor Attacks Enhanced by Sharpness Aware Minimization},
  author = {Zhang, Mingda and Zhu, Mingli and Zhu, Zihao and Wu, Baoyuan},
  journal = {arXiv preprint},
  year = {2024},
}

@article{zhu2024earbench,
  title = {EARBench: Towards Evaluating Physical Risk Awareness for Task Planning of Foundation Model-based Embodied AI Agents},
  author = {Zhu, Zihao and Wu, Bingzhe and Zhang, Zhengyou and Han, Lei and Liu, Qingshan and Wu, Baoyuan},
  year = {2024},
  journal = {arXiv preprint},
}

@inproceedings{zhu2024vdc,
  title = {VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models},
  author = {Zhu, Zihao and Zhang, Mingda and Wei, Shaokui and Wu, Bingzhe and Wu, Baoyuan},
  booktitle = {International Conference on Learning Representations},
  year = {2024},
}

@article{zheng2023blackboxbench,
  title = {BlackboxBench: A Comprehensive Benchmark of Black-box Adversarial Attacks},
  author = {Zheng, Meixi and Yan, Xuanchen and Zhu, Zihao and Chen, Hongrui and Wu, Baoyuan},
  journal = {arXiv preprint},
  year = {2023},
}

@article{wu2023defenses,
  title = {Defenses in adversarial machine learning: A survey},
  author = {Wu, Baoyuan and Wei, Shaokui and Zhu, Mingli and Zheng, Meixi and Zhu, Zihao and Zhang, Mingda and Chen, Hongrui and Yuan, Danni and Liu, Li and Liu, Qingshan},
  journal = {arXiv preprint},
  year = {2023},
}

@article{zhu2023boosting,
  title = {Boosting backdoor attack with a learnable poisoning sample selection strategy},
  author = {Zhu, Zihao and Zhang, Mingda and Wei, Shaokui and Shen, Li and Fan, Yanbo and Wu, Baoyuan},
  journal = {arXiv preprint},
  year = {2023},
}

@article{wu2023attacks,
  title = {Attacks in adversarial machine learning: A systematic survey from the life-cycle perspective},
  author = {Wu, Baoyuan and Zhu, Zihao and Liu, Li and Liu, Qingshan and He, Zhaofeng and Lyu, Siwei},
  journal = {arXiv preprint},
  year = {2023},
}

@inproceedings{wu2022backdoorbench,
  title = {BackdoorBench: A Comprehensive Benchmark of Backdoor Learning},
  author = {Wu, Baoyuan and Chen, Hongrui and Zhang, Mingda and Zhu, Zihao and Wei, Shaokui and Yuan, Danni and Zha, Hongyuan},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2022},
}

@inproceedings{zhu2022shallow,
  title = {From Shallow to Deep: Compositional Reasoning over Graphs for Visual Question Answering},
  author = {Zhu, Zihao},
  booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing},
  year = {2022},
}

@article{yu2020cross,
  title = {Cross-Modal Knowledge Reasoning for Knowledge-based Visual Question Answering},
  author = {Yu, Jing and Zhu, Zihao and Wang, Yujing and Zhang, Weifeng and Hu, Yue and Tan, Jianlong},
  journal = {Pattern Recognition},
  year = {2020},
}

@inproceedings{zhu2020mucko,
  title = {Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering},
  author = {Zhu, Zihao and Yu, Jing and Wang, Yujing and Sun, Yajing and Hu, Yue and Wu, Qi},
  booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence},
  year = {2020},
}