Hao Cheng

According to our database, Hao Cheng authored at least 33 papers between 2019 and 2025.

Collaborative distances:

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

2025

Humanoid Occupancy: Enabling A Generalized Multimodal Occupancy Perception System on Humanoid Robots.

Wei Cui, Haoyu Wang, Wenkang Qin, Yijie Guo, Gang Han, Wen Zhao, Jiahang Cao, Zhang Zhang, Jiaru Zhong, Jingkai Sun, Pihai Sun, Shuai Shi, Botuo Jiang, Jiahao Ma, Jiaxu Wang, Hao Cheng, Zhichao Liu, Yang Wang, Zheng Zhu, Guan Huang, Jian Tang, Qiang Zhang

CoRR, July, 2025

Occupancy World Model for Robots.

Zhang Zhang, Qiang Zhang, Wei Cui, Shuai Shi, Yijie Guo, Gang Han, Wen Zhao, Jingkai Sun, Jiahang Cao, Jiaxu Wang, Hao Cheng, Xiaozhu Ju, Zhengping Che, Renjing Xu, Jian Tang

CoRR, May, 2025

Modality-Composable Diffusion Policy via Inference-Time Distribution-level Composition.

Jiahang Cao, Qiang Zhang, Hanzhong Guo, Jiaxu Wang, Hao Cheng, Renjing Xu

CoRR, March, 2025

TruthPrInt: Mitigating LVLM Object Hallucination Via Latent Truthful-Guided Pre-Intervention.

Jinhao Duan, Fei Kong, Hao Cheng, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu

CoRR, March, 2025

LiPS: Large-Scale Humanoid Robot Reinforcement Learning with Parallel-Series Structures.

Qiang Zhang, Gang Han, Jingkai Sun, Wen Zhao, Jiahang Cao, Jiaxu Wang, Hao Cheng, Lingfeng Zhang, Yijie Guo, Renjing Xu

CoRR, March, 2025

Spiking Diffusion Models.

Jiahang Cao, Hanzhong Guo, Ziqing Wang, Deming Zhou, Hao Cheng, Qiang Zhang, Renjing Xu

IEEE Trans. Artif. Intell., January, 2025

Tune In, Act Up: Exploring the Impact of Audio Modality-Specific Edits on Large Audio Language Models in Jailbreak.

Erjia Xiao, Hao Cheng, Jing Shao, Jinhao Duan, Kaidi Xu, Le Yang, Jindong Gu, Renjing Xu

CoRR, January, 2025

2024

Uncovering Vision Modality Threats in Image-to-Image Tasks.

Hao Cheng, Erjia Xiao, Jiayan Yang, Jiahang Cao, Qiang Zhang, Jize Zhang, Kaidi Xu, Jindong Gu, Renjing Xu

CoRR, 2024

Manipulation Facing Threats: Evaluating Physical Vulnerabilities in End-to-End Vision Language Action Models.

Hao Cheng, Erjia Xiao, Chengyuan Yu, Zhao Yao, Jiahang Cao, Qiang Zhang, Jiaxu Wang, Mengshu Sun, Kaidi Xu, Jindong Gu, Renjing Xu

CoRR, 2024

Mamba Policy: Towards Efficient 3D Diffusion Policy with Hybrid Selective State Models.

Jiahang Cao, Qiang Zhang, Jingkai Sun, Jiaxu Wang, Hao Cheng, Yulin Li, Jun Ma, Yecheng Shao, Wen Zhao, Gang Han, Yijie Guo, Renjing Xu

CoRR, 2024

Mamba as Decision Maker: Exploring Multi-scale Sequence Modeling in Offline Reinforcement Learning.

Jiahang Cao, Qiang Zhang, Ziqing Wang, Jiaxu Wang, Hao Cheng, Yecheng Shao, Wen Zhao, Gang Han, Yijie Guo, Renjing Xu

CoRR, 2024

Typography Leads Semantic Diversifying: Amplifying Adversarial Transferability across Multimodal Large Language Models.

Hao Cheng, Erjia Xiao, Jiahang Cao, Le Yang, Kaidi Xu, Jindong Gu, Renjing Xu

CoRR, 2024

Unveiling Typographic Deceptions: Insights of the Typographic Vulnerability in Large Vision-Language Model.

Hao Cheng, Erjia Xiao, Jindong Gu, Le Yang, Jinhao Duan, Jize Zhang, Jiahang Cao, Kaidi Xu, Renjing Xu

CoRR, 2024

Spiking Denoising Diffusion Probabilistic Models.

Jiahang Cao, Ziqing Wang, Hanzhong Guo, Hao Cheng, Qiang Zhang, Renjing Xu

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Spiking Neural Network as Adaptive Event Stream Slicer.

Jiahang Cao, Mingyuan Sun, Ziqing Wang, Hao Cheng, Qiang Zhang, Shibo Zhou, Renjing Xu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Gaining the Sparse Rewards by Exploring Lottery Tickets in Spiking Neural Networks.

Hao Cheng, Jiahang Cao, Erjia Xiao, Mengshu Sun, Renjing Xu

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

DONE: Dynamic Neural Representation Via Hyperplane Neural ODE.

Jiaxu Wang, Bo Xu, Hao Cheng, Renjing Xu

Proceedings of the IEEE International Conference on Acoustics, 2024

Unveiling Typographic Deceptions: Insights of the Typographic Vulnerability in Large Vision-Language Models.

Hao Cheng, Erjia Xiao, Jindong Gu, Le Yang, Jinhao Duan, Jize Zhang, Jiahang Cao, Kaidi Xu, Renjing Xu

Proceedings of the Computer Vision - ECCV 2024, 2024

ACT-Diffusion: Efficient Adversarial Consistency Training for One-Step Diffusion Models.

Fei Kong, Jinhao Duan, Lichao Sun, Hao Cheng, Renjing Xu, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models.

Jinhao Duan, Hao Cheng, Shiqi Wang, Alex Zavalny, Chenan Wang, Renjing Xu, Bhavya Kailkhura, Kaidi Xu

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

ACT: Adversarial Consistency Models.

Fei Kong, Jinhao Duan, Lichao Sun, Hao Cheng, Renjing Xu, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu

CoRR, 2023

Pursing the Sparse Limitation of Spiking Deep Learning Structures.

Hao Cheng, Jiahang Cao, Erjia Xiao, Mengshu Sun, Le Yang, Jize Zhang, Xue Lin, Bhavya Kailkhura, Kaidi Xu, Renjing Xu

CoRR, 2023

Gaining the Sparse Rewards by Exploring Binary Lottery Tickets in Spiking Neural Network.

Hao Cheng, Jiahang Cao, Erjia Xiao, Pu Zhao, Mengshu Sun, Jiaxu Wang, Jize Zhang, Xue Lin, Bhavya Kailkhura, Kaidi Xu, Renjing Xu

CoRR, 2023

RBFormer: Improve Adversarial Robustness of Transformer by Robust Bias.

Hao Cheng, Jinhao Duan, Hui Li, Lyutianyang Zhang, Jiahang Cao, Ping Wang, Jize Zhang, Kaidi Xu, Renjing Xu

CoRR, 2023

Shifting Attention to Relevance: Towards the Uncertainty Estimation of Large Language Models.

Jinhao Duan, Hao Cheng, Shiqi Wang, Chenan Wang, Alex Zavalny, Renjing Xu, Bhavya Kailkhura, Kaidi Xu

CoRR, 2023

Improve Video Representation with Temporal Adversarial Augmentation.

Jinhao Duan, Quanfu Fan, Hao Cheng, Xiaoshuang Shi, Kaidi Xu

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

RBFormer: Improve Adversarial Robustness of Transformers by Robust Bias.

Hao Cheng, Jinhao Duan, Hui Li, Jiahang Cao, Ping Wang, Lyutianyang Zhang, Jize Zhang, Kaidi Xu, Renjing Xu

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

Efficient Multi-Prize Lottery Tickets: Enhanced Accuracy, Training, and Inference Speed.

Hao Cheng, Pu Zhao, Yize Li, Xue Lin, James Diffenderfer, Ryan A. Goldhahn, Bhavya Kailkhura

CoRR, 2022

More or Less (MoL): Defending against Multiple Perturbation Attacks on Deep Neural Networks through Model Ensemble and Compression.

Hao Cheng, Kaidi Xu, Zhengang Li, Pu Zhao, Chenan Wang, Xue Lin, Bhavya Kailkhura, Ryan A. Goldhahn

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2022

2021

Mixture of Robust Experts (MoRE): A Flexible Defense Against Multiple Perturbations.

Hao Cheng, Kaidi Xu, Chenan Wang, Xue Lin, Bhavya Kailkhura, Ryan A. Goldhahn

CoRR, 2021

2020

Defending against Backdoor Attack on Deep Neural Networks.

Hao Cheng, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Pu Zhao, Xue Lin

CoRR, 2020

2019

Second Rethinking of Network Pruning in the Adversarial Setting.

Shaokai Ye, Kaidi Xu, Sijia Liu, Hao Cheng, Jan-Henrik Lambrechts, Huan Zhang, Aojun Zhou, Kaisheng Ma, Yanzhi Wang, Xue Lin

CoRR, 2019

Adversarial Robustness vs. Model Compression, or Both?

Shaokai Ye, Xue Lin, Kaidi Xu, Sijia Liu, Hao Cheng, Jan-Henrik Lambrechts, Huan Zhang, Aojun Zhou, Kaisheng Ma, Yanzhi Wang

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019