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Ce Zhang

Master's Student
Carnegie Mellon University
cezhang (at) cs.cmu.edu


About Me

Hi there! I’m Ce Zhang, a master’s student in the Machine Learning Department at Carnegie Mellon University (CMU), advised by Prof. Katia Sycara. Prior to this, I received my B.Eng. in Communication Engineering from Southern University of Science and Technology (SUSTech), where I worked under the supervision of Prof. Zhihai He. My current research interest lie in vision-language models and scene understanding.

Research Interests

News

Publications

  1. Preprint
    Incorporating Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
    Ce Zhang*, Zifu Wan*, Zhehan Kan, Martin Ma, Simon Stepputtis, Deva Ramanan, Russ Salakhutdinov, Louis-Philippe Morency, Katia Sycara, Yaqi Xie (*Equal contribution)
    NeurIPS 2024 Workshop on Responsibly Building the Next Generation of Multimodal Foundational Models.
    Preprint, under review.

  2. WACV 2025
    Enhancing Vision-Language Few-Shot Adaptation with Negative Learning
    Ce Zhang, Simon Stepputtis, Katia Sycara, Yaqi Xie
    IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.
    Also at ICLR 2024 Workshop on Mathematical and Empirical Understanding of Foundation Models.
    Tucson, AZ, US, February 28 - March 4, 2025
    PDF

  3. NeurIPS 2024
    Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models
    Ce Zhang, Simon Stepputtis, Katia Sycara, Yaqi Xie
    Conference on Neural Information Processing Systems (NeurIPS), 2024.
    Also at ICML 2024 Workshop on Foundation Models in the Wild.
    Vancouver, Canada, December 10-15, 2024
    PDF Website GitHub Stars

  4. CVPR 2024
    HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation
    Ce Zhang, Simon Stepputtis, Joseph Campbell, Katia Sycara, Yaqi Xie
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
    Also at NeurIPS 2023 New Frontiers in Graph Learning Workshop.
    Seattle, WA, US, June 17-21, 2024
    PDF Supplementary Website Video GitHub Stars

  5. IEEE TAI
    Critical Sampling for Robust Evolution Operator Learning of Unknown Dynamical Systems
    Ce Zhang, Kailiang Wu, Zhihai He
    IEEE Transactions on Artificial Intelligence, 2023;
    Also at First Workshop on Out-of-Distribution Generalization in Robotics at CoRL 2023.
    Atlanta, GA, US, November 6-9, 2023
    PDF

  6. BMVC 2023
    BDC-Adapter: Brownian Distance Covariance for Better Vision-Language Reasoning
    Yi Zhang*, Ce Zhang*, Zihan Liao, Yushun Tang, Zhihai He (*Equal contribution)
    British Machine Vision Conference (BMVC), 2023.
    Aberdeen, UK, November 20-24, 2023
    PDF Supplementary Website Video

  7. CVPR 2023
    Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation
    Yushun Tang, Ce Zhang, Heng Xu, Shuoshuo Chen, Jie Cheng, Luziwei Leng, Qinghai Guo, Zhihai He
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
    Vancouver, Canada, June 18-22, 2023
    PDF Supplementary Video

  8. CVPR 2023
    Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation
    Zhehan Kan, Shuoshuo Chen, Ce Zhang, Yushun Tang, Zhihai He
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
    Vancouver, Canada, June 18-22, 2023
    PDF Supplementary Video

  9. AAAI 2024
    Concept-Guided Prompt Learning for Generalization in Vision-Language Models
    Yi Zhang, Ce Zhang, Ke Yu, Yushun Tang, Zhihai He
    AAAI Conference on Artificial Intelligence (AAAI), 2024.
    Vancouver, Canada, February 22-25, 2024
    PDF Video

  10. WACV 2024
    Learning to Adapt CLIP for Few-Shot Monocular Depth Estimation
    Xueting Hu, Ce Zhang, Yi Zhang, Bowen Hai, Ke Yu, Zhihai He
    IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.
    Waikoloa, HI, US, January 4-8, 2024
    PDF Video

Honors and Awards

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