Ph.D. student, MMLab, The Chinese University of Hong Kong
chentang [AT] link.cuhk.edu.hk / tangchen18 [AT] outlook.com
[Google Scholar] [OpenReview] [LinkedIn] [GitHub]
I am currently a Ph.D. student at the Multimedia Laboratory (MMLab), The Chinese University of Hong Kong, co-supervised by Prof. Wanli Ouyang and Prof. Xiangyu Yue. Before joining CUHK, I was a research assistant in the Department of Computer Science and Technology at Tsinghua University, working with Prof. Wenwu Zhu, Prof. Zhi Wang, and Prof. Yuan Meng. I received my Master's degree in Computer Technology from Tsinghua University, advised by Prof. Zhi Wang. I won the Distinguished Master's Thesis Award of Tsinghua.
I was a visiting student at AIoT Lab, Institute for AI Industry Research (AIR) at Tsinghua University, working with Prof. Yuanchun Li and Prof. Yunxin Liu. Prior to that, I spent a wonderful year as a research intern in the System and Networking Research Group at Microsoft Research Asia, working with Dr. Li Lyna Zhang. I also was a visiting student at Peng Cheng National Laboratory (PCL). I am a member of the IEEE Digital Retina Systems Working Group (3161 WG), and have served as a reviewer for CVPR, ECCV, ACM Multimedia, ICLR, NeurIPS, and AAAI.
My research interests are in AI for science, efficient learning, multimodal learning, and generative learning. Feel free to contact me if you are interested in my research.
[2024/07] One paper got accepted to ECCV 2024.
[2024/02] Two paper got accepted to CVPR 2024 and ICLR 2024 PML4LRS Workshop, respectively.
[2023/07] Three papers got accepted to ICCV 2023, ECML-PKDD 2023, and ACM Multimedia 2023, respectively.
[2023/06] I earned my Master's degree along with the Distinguished Master's Thesis Award!
Expansive Supervision for Neural Radiance Field
Weixiang Zhang, Shuzhao Xie, Shijia Ge, Wei Yao, Chen Tang, Zhi Wang
Preprint, 2024
[PDF]
PRANCE: Joint Token-Optimization and Structural Channel-Pruning for Adaptive ViT Inference
Ye Li*, Chen Tang*, Yuan Meng, Jiajun Fan, Zenghao Chai, Xinzhu Ma, Zhi Wang, Wenwu Zhu
In submission to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
[PDF]
[Code]
MesonGS: Post-training Compression of 3D Gaussians via Efficient Attribute Transformation
Shuzhao Xie, Weixiang Zhang, Chen Tang, Yunpeng Bai, Rongwei Lu, Shijia Ge, Zhi Wang
[ECCV'24] European Conference on Computer Vision, 2024
[PDF]
[Supp]
[Project]
[Poster]
[Code]
Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers
Lei Chen, Yuan Meng, Chen Tang, Xinzhu Ma, Jingyan Jiang, Xin Wang, Zhi Wang, Wenwu Zhu
Preprint, 2024
[PDF]
[Code]
RFQuant: Retraining-free Model Quantization via One-Shot Weight-Coupling Learning
Chen Tang*, Yuan Meng*, Jiacheng Jiang, Shuzhao Xie, Rongwei Lu, Xinzhu Ma, Zhi Wang, Wenwu
Zhu
[CVPR'24] IEEE Conference on Computer Vision and Pattern Recognition, 2024
[PDF]
[Supp]
[Poster]
[Code]
One QuantLLM for ALL: Fine-tuning Quantized LLMs Once for Efficient
Deployments
Ke Yi, Yuhui Xu, Heng Chang, Chen Tang, Yuan Meng, Tong Zhang, Jia Li
Preprint, 2024
[PDF]
[Code]
TMPQ-DM: Joint Timestep Reduction and Quantization Precision
Selection for Efficient Diffusion Models
Haojun Sun*, Chen Tang*, Zhi Wang, Yuan Meng, Jingyan Jiang, Xinzhu Ma, Wenwu Zhu
Preprint, 2024
[PDF]
[Project]
[Code]
STAR: Skeleton-aware Text-based 4D Avatar
Generation with In-Network Motion Retargeting
Zenghao Chai, Chen Tang, Yongkang Wong, Mohan Kankanhalli
In submission to IEEE Transactions on Visualization and Computer Graphics (TVCG), 2024
[PDF]
[Project]
[Code]
Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and
Toolbox
Yijun Liu, Yuan Meng, Fang Wu, Shenhao Peng, Hang Yao, Chaoyu Guan, Chen Tang, Xinzhu Ma,
Zhi Wang, Wenwu Zhu
Preprint, 2024
[PDF]
[Toolbox]
Investigating the Impact of Quantization on Adversarial Robustness
Qun Li, Yuan Meng, Chen Tang, Jiacheng Jiang, Zhi Wang
[ICLR PML4LRS'24] International Conference on Learning Representations (Workshop on Practical ML
for Limited Resource Settings), 2024
[PDF]
DAGC: Data-aware Adaptive Sparsification Gradient Compression for Distributed Machine
Learning in Mobile Computing
Rongwei Lu, Yutong Jiang, Yinan Mao, Chen Tang, Bin Chen, Laizhong Cui, Zhi Wang
In submission to IEEE Transactions on Mobile Computing (TMC), 2024
[PDF]
[Code]
Knowledge Soft Integration for Multimodal Recommendation
Kai Ouyang*, Chen Tang*, Wenhao Zheng, Xiangjin Xie, Xuanji Xiao, Jian Dong, Hai-tao Zheng,
Zhi Wang
In submission to IEEE Transactions on Multimedia (TMM), 2024
[PDF]
Click-aware Structure Transfer with Sample Weight Assignment for Post-Click
Conversion Rate
Estimation
Kai Ouyang, Wenhao Zheng, Chen Tang, Xuanji Xiao, Hai-tao Zheng
[ECML-PKDD'23] European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases, 2023 [PDF]
[Code]
SEAM: Searching Transferable Mixed-Precision Quantization Policy through Large Margin
Regularization
Chen Tang, Kai Ouyang, Zenghao Chai, Yunpeng Bai, Yuan Meng, Zhi Wang, Wenwu Zhu
[ACM MM'23] ACM International Conference on Multimedia, 2023
[PDF]
ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on
Diverse
Mobile Devices
Chen Tang*, Li Lyna Zhang*, Huiqiang Jiang, Jiahang
Xu, Ting Cao, Quanlu Zhang, Yuqing Yang, Zhi Wang, Mao Yang
[ICCV'23] International Conference on Computer Vision, 2023
[PDF]
[Supp]
[Poster]
[Code]
Mixed-Precision Network Quantization via Learned Layer-wise Importance
Chen Tang*, Kai Ouyang*, Zhi Wang, Yifei Zhu, Wen Ji,
Yaowei Wang, Wenwu Zhu
[ECCV'22] European Conference on Computer Vision, 2022
[PDF]
[Supp]
[Project]
[Poster]
[Code]
Arbitrary Bit-width Network: A Joint Layer-Wise Quantization and Adaptive Inference
Approach
Chen Tang, Haoyu Zhai, Kai Ouyang, Zhi Wang, Yifei Zhu, Wenwu Zhu
[ACM MM'22] ACM International Conference on Multimedia, 2022
[PDF]
Social-aware Sparse Attention Network for Session-based Social
Recommendation
Kai Ouyang, Xianghong Xu, Chen Tang, Wang Chen, Hai-tao Zheng
[Findings of EMNLP'22] Findings of Conference on Empirical Methods in Natural Language
Processing, 2022 [PDF]
Research Intern (Remote), Shanghai Artificial Intelligence Laboratory (Aug. 2024 -- Present)
Research Assistant, Department of Computer Science and Technology, Tsinghua University (Aug. 2023 -- Jul. 2024)
Research Intern, Institute for AI Industry Research, Tsinghua University (Nov. 2023 -- Apr. 2024)
Research Intern, Microsoft Research Asia (Nov. 2022 -- Nov. 2023)
Visiting Student, Peng Cheng Laboratory (Apr. 2022 -- Nov. 2022)
Journal Reviewer: Neural Networks
Conference Reviewer (Program Committee): AAAI (2024), ACM MM (2024), CVPR (2023, 2024), ECCV (2022, 2024), ICLR (2024, 2025), NeurIPS (2023, 2024), ECAI (2023)
Distinguished Master's Thesis Award, Tsinghua University, 2023
Internship Award (Second Prize), Tsinghua University, 2023
First Prize Scholarship (Huiyan Scholarship), Tsinghua University, 2022
Star of Tomorrow Excellent Internship Award, Microsoft Research Asia, 2022
Merit Undergraduate Student, 2019
Outstanding Undergraduate Student, 2018
Code from Han Hu