I am currently a Full Professor at Hefei University of Technology.

I received my Ph.D. degree from The Chinese University of Hong Kong (CUHK) in 2022, under the supervision of Prof. Jiaya Jia and Prof. Bei Yu. Prior to that, I obtained my B.E. degree in Computer Science from Shandong University in 2018. I also spent two wonderful years at Nanyang Technological University (NTU), Singapore. CV

Research

Data-centric AI plays a crucial role in advancing towards Artificial General Intelligence (AGI). My research focuses on developing novel algorithms and theoretical foundations — such as contrastive learning and generative learning — to more effectively leverage data for enhancing model generalization and robustness.

In addition, my team actively explores multi-modal alignment and robustness in large models, including LLMs and VLMs. Our work addresses critical challenges such as jailbreak attacks, adversarial robustness, and hallucination mitigation.

I am also broadly interested in emerging machine learning topics, including AI for science and 3D modeling, and always enthusiastic about tackling new challenges in these domains.

Selected Publications [Google Scholar]

* represents equal contributions

• Decoupled Kullback-Leibler Divergence Loss
  Jiequan Cui, Zhuotao Tian, Zhisheng Zhong, Xiaojuan Qi, Bei Yu, Hanwang Zhang.
  Conference on Neural Information Processing Systems (NeurIPS), 2024.
  paper code

• Classes Are Not Equal: An Empirical Study on Image Recognition Fairness
  Jiequan Cui, Beier Zhu, Xin Wen, Xiaojuan Qi, Bei Yu, Hanwang Zhang.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  paper code

• Genralized Parametric Contrastive Learning
  Jiequan Cui, Zhisheng Zhong, Zhuotao Tian, Shu Liu, Bei Yu, Jiaya Jia.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  paper code

• ResLT: Residual Learning for Long-tailed Recognition
  Jiequan Cui, Shu Liu, Zhuotao Tian, Zhisheng Zhong, Jiaya Jia.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
  paper code

• Parametric Contrastive Learning
  Jiequan Cui, Zhisheng Zhong, Shu Liu, Bei Yu, Jiaya Jia.
  IEEE International Conference on Computer Vision (ICCV), 2021.
  paper code

• Learnable Boundary Guided Adversarial Training
  Jiequan Cui, Shu Liu, Liwei Wang, Jiaya Jia.
  IEEE International Conference on Computer Vision (ICCV), 2021.
  paper code

Full Publications [Google Scholar]

* represents equal contributions

• Learnable Feature Patches and Vectors for Boosting Low-light Image Enhancement without External Knowledge
  Xiaogang Xu, Jiafei Wu, Qingsen Yan, Jiequan Cui, Richang Hong, Bei Yu.
  IEEE International Conference on Computer Vision (ICCV), 2025
  paper

• Aligned Contrastive Loss for Long-Tailed Recognition
  Jiali Ma, Jiequan Cui, Maeno Kazuki, Lakshmi Subramanian, Karlekar Jayashree, Sugiri Pranata, Hanwang Zhang.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR workshop), 2025.
  paper

• Project-Probe-Aggregate: Efficient Fine-Tuning for Group Robustness
  Beier Zhu, Jiequan Cui, Hanwang Zhang, Chi Zhang. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
  paper

• CARE Transformer: Mobile-Friendly Linear Visual Transformer via Decoupled Dual Interaction
  Yuan Zhou, Qingshan Xu, Jiequan Cui, Junbao Zhou, Jing Zhang, Richang Hong, Hanwang Zhang.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
  paper

• Robust Fine-tuning of Zero-shot Models via Variance Reduction
  Beier Zhu, Jiequan Cui, Hanwang Zhang.
  Conference on Neural Information Processing Systems (NeurIPS), 2024.
  paper

• Typicalness-Aware Learning for Failure Detection
  Yijun Liu, Jiequan Cui, Zhuotao Tian, Senqiao Yang, Qingdong He, Xiaoling Wang, Jingyong Su.
  Conference on Neural Information Processing Systems (NeurIPS), 2024.
  paper

• Decoupled Kullback-Leibler Divergence Loss
  Jiequan Cui, Zhuotao Tian, Zhisheng Zhong, Xiaojuan Qi, Bei Yu, Hanwang Zhang.
  Conference on Neural Information Processing Systems (NeurIPS), 2024.
  paper code

• Instruction Tuning-free Visual Token Complement for Multimodal LLMs
  Dongsheng Wang, Jiequan Cui, Miaoge Li, Wang Lin, Bo Chen, Hanwang Zhang.
  European Conference on Computer Vision (ECCV), 2024.
  paper

• Classes Are Not Equal: An Empirical Study on Image Recognition Fairness
  Jiequan Cui, Beier Zhu, Xin Wen, Xiaojuan Qi, Bei Yu, Hanwang Zhang.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  paper code

• Doubly Abductive Counterfactual Inference for Text-based Image Editing
  Xue Song, Jiequan Cui, Hanwang Zhang, Jingjing Chen, Richang Hong, YuGang Jiang.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  paper code

• Genralized Parametric Contrastive Learning
  Jiequan Cui, Zhisheng Zhong, Zhuotao Tian, Shu Liu, Bei Yu, Jiaya Jia.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  paper code

• Understanding Imbalanced Semantic Segmentation Through Neural Collapse
  Zhisheng Zhong*, Jiequan Cui*, Yibo Yang*, Xiaoyang Wu, Xiaojuan Qi, Xiangyu Zhang, Jiaya Jia.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  paper

• Learning Context-aware Classifier for Semantic Segmentation
  Zhuotao Tian, Jiequan Cui, Li Jiang, Xiaojuan Qi, Xin Lai, Yixin Chen, Shu Liu, Jiaya Jia.
  AAAI Conference on Artificial Intelligence (AAAI), 2023.
  paper

• ResLT: Residual Learning for Long-tailed Recognition
  Jiequan Cui, Shu Liu, Zhuotao Tian, Zhisheng Zhong, Jiaya Jia.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
  paper code

• Parametric Contrastive Learning
  Jiequan Cui, Zhisheng Zhong, Shu Liu, Bei Yu, Jiaya Jia.
  IEEE International Conference on Computer Vision (ICCV), 2021.
  paper code

• Learnable Boundary Guided Adversarial Training
  Jiequan Cui, Shu Liu, Liwei Wang, Jiaya Jia.
  IEEE International Conference on Computer Vision (ICCV), 2021.
  paper code

• Improving Calibration for Long-Tailed Recognition
  Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  paper code

• Fast and Practical Neural Architecture Search
  Jiequan Cui, Pengguang Chen, Ruiyu Li, Shu Liu, Xiaoyong Shen, Jiaya Jia.
  IEEE International Conference on Computer Vision (ICCV), 2019.
  paper code