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I am a final-year Ph.D. candidate focusing on computer vision and machine learning at Peking University, where my advisor is Prof. Yadong Mu. Before that, I obtained my B.S. degree in Computer Science from Peking University. Email: sunzc [at] pku [dot] edu [dot] cn CV / Google Scholar / LinkedIn / Github / Twitter |
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My research spans Generative Models and Continual Learning. My short-term goal is to improve generative models from the continual learning perspective (e.g. efficiency, knowledge sharing). My long-term goal is to enable generative models to learn continually (through new paradigms such as flow-based models and equilibrium models). |
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Yang Jin, Zhicheng Sun, Ningyuan Li, Kun Xu, Kun Xu, Hao Jiang, Nan Zhuang, Quzhe Huang, Yang Song, Yadong Mu, Zhouchen Lin Preprint, 2024 project page / paper / code / bibtex We design a unified flow matching objective that jointly generates and decompresses visual content across pyramidal representations. |
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Jinghan Li, Zhicheng Sun, Fei Li, Cao Sheng, Jiazhong Yu, Yadong Mu Preprint, 2024 paper / code / bibtex We propose an equilibrium model-based LLM planner that is capable of self-refining its plan with external and internal feedback. |
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Zhicheng Sun, Zhenhao Yang, Yang Jin, Haozhe Chi, Kun Xu, Kun Xu, Liwei Chen, Hao Jiang, Yang Song, Kun Gai, Yadong Mu NeurIPS, 2024 paper / code / bibtex We introduce a training-free approach to personalizing rectified flow, based on a fixed-point formulation of classifier guidance. |
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Yang Jin, Zhicheng Sun, Kun Xu, Kun Xu, Liwei Chen, Hao Jiang, Quzhe Huang, Chengru Song, Yuliang Liu, Di Zhang, Yang Song, Kun Gai, Yadong Mu ICML, 2024 (Oral) project page / paper / code / bibtex We present a multimodal LLM capable of both comprehending and generating videos, based on an efficient decomposed video representation. |
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Zhicheng Sun, Jinghan Li, Yadong Mu CVPR, 2024 paper / code / bibtex We develop an open world object detector that exploits feature and prediction orthogonality to continually identify unknown objects. |
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Hanwen Liu, Zhicheng Sun, Yadong Mu CVPR, 2024 paper / code / bibtex We forge unlearnable examples against diffusion models with a robust watermarking method that focuses on the most influential pixels. |
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Zhicheng Sun, Yadong Mu NeurIPS, 2023 (Spotlight) paper / code / bibtex We propose a novel rewiring approach by permuting hidden neurons, allowing for structural plasticity in continual reinforcement learning. |
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Zhicheng Sun, Yadong Mu, Gang Hua CVPR, 2023 paper / arXiv / code / bibtex We identify a new class of second-order influence functions in replay-based continual learning, and address it with a regularized selection strategy. |
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Zhicheng Sun, Yadong Mu ACM Multimedia, 2022 paper / code / bibtex We use adaptively-chosen patches (rather than whole images) to pilot the forgetting-resistant distillation for lifelong person re-identification. |
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