Ce Zhang
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
I aim to enhance the adaptability and reliability of multi-modal models, pushing the boundaries of what they can achieve in real-world applications. My vision focuses on tackling pivotal challenges, including:
- How can we responsibly deploy multi-modal models while mitigating real-world societal concerns, such as mitigating misinformation and hallucinations, promoting fairness, and overcoming challenges with compositional reasoning?
- How can we enable a broader adaptability of these models to diverse real-world domains, such as robotics and healthcare, by leveraging resource-efficient fine-tuning, test-time adaptation, and continual learning?
- How can these models seamlessly interact with humans and their environments, such as advancing capabilities in human-object interaction detection, 3D visual reasoning, and video understanding?
News
- [Jan. 2025] Our paper “Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models” is accepted to ICLR 2025.
- [Oct. 2024] Our paper “Enhancing Vision-Language Few-Shot Adaptation with Negative Learning” is accepted to WACV 2025.
- [Sep. 2024] Our paper “Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models” is accepted to NeurIPS 2024.
- [Feb. 2024] Our paper “HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation” is accepted to CVPR 2024.
- [Sep. 2023] Our paper “Learning to Adapt CLIP for Few-Shot Monocular Depth Estimation” is accepted to WACV 2024.
Publications
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ICLR 2025
International Conference on Learning Representations (ICLR), 2025.Also at NeurIPS 2024 Workshop on Responsibly Building the Next Generation of Multimodal Foundational Models.Singapore, April 24-28, 2025 -
WACV 2025
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 -
NeurIPS 2024
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 -
CVPR 2024
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 -
IEEE TAI
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 -
BMVC 2023
British Machine Vision Conference (BMVC), 2023.Aberdeen, UK, November 20-24, 2023 -
CVPR 2023
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.Vancouver, Canada, June 18-22, 2023 -
CVPR 2023
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.Vancouver, Canada, June 18-22, 2023 -
AAAI 2024
AAAI Conference on Artificial Intelligence (AAAI), 2024.Vancouver, Canada, February 22-25, 2024 -
WACV 2024
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.Waikoloa, HI, US, January 4-8, 2024
Honors and Awards
- Top 10 Summa Cum Laude Graduates, Southern University of Science and Technology, June 2023
- Chinese National Scholarship, Ministry of Education of the People’s Republic of China, Novermber 2022
Services
- Journal Reviewer: IEEE TCSVT, IEEE TMM, IEEE TAI
- Conference Reviewer: ICLR 2025, WACV 2025, ICASSP 2025, BMVC 2024 (Outstanding Reviewer), ICME 2024
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