Yan Zhong 钟岩

Yan Zhong 钟岩

Doctoral Candidate, PKU

🌞 About Me

I am a Ph.D. candidate from National Engineering Research Center of Visual Technology, School of Computer Science and School of Mathematical Sciences, Peking University (PKU), Beijing, China, supervised by Prof. Ming Jiang and Assoc. Prof. Tingting Jiang. Before joining PKU, I received my M.S. degree at School of Artificial Intelligence and Data Science, University of Science and Technology of China (USTC), Hefei, China, in 2022, supervised by Prof. Huanhuan Chen. I received my B.S. degree from School of Mathematics and Statistics, Northwestern PolyPtechnical University (NWPU), Xi’an, China, in 2019, supervised by Prof. Hongchan Zheng.

I am currently affiliated with the Multimedia and Interactive Computing Lab (MICL) as a visiting student in College of Computing and Data Science (CCDS), Nanyang Technological University (NTU), Singapore, where we focus on pushing the boundaries of Computer Vision & Language (CVL) and Graphics & Interactive Computing (GIC) research. I am fortunate to be advised by Prof. Weisi Lin in MICL Lab.

My research interest encompass a wide range of areas, including Machine/Deep Learning, Computer Vision, Quality Assessment, and the applications of State Space Models (SSM) and Large Language Models (LLMs) in vision. For anything about the research, resources, and other related matters, please feel free to contact me via Email.

📖 Educations

  • 2022.09 - 2026.06, Peking University, Ph.D.
    • Applied Mathematics, School of Mathematical Sciences
  • 2019.09 - 2022.06, University of Science and Technology of China, M.S.
    • Data Science (Computer Science and Technology), School of Artificial Intelligence and Data Science
  • 2015.09 - 2019.06, Northwestern PolyPtechnical University, B.S.
    • Information and Computing Science, School of Mathematics and Statistics

💻 Research Interests

  • Machine / Deep Learning
  • Computer Vision and Quality Assessment
  • Multimodal Large Language Models

📝 Publications

Papers

  1. Yan Zhong, Xinping Zhao, Li Zhang, Xinyuan Song, Tingting Jiang. Adaptive Prompt Learning for Blind Image Quality Assessment with Multi-modal Mixed-datasets Training. The 33rd ACM International Conference on Multimedia (ACM MM’25), Oct 27-31, 2025, Dublin, Ireland.
  2. Jianhui Wang, Yangfan He, Yan Zhong, Xinyuan Song, Jiayi Su, Yuheng Feng, Ruoyu Wang, Hongyang He, Wenyu Zhu, Xinhang Yuan, Miao Zhang, Keqin Li, Jiaqi Chen, TIANYU SHI, Xueqian Wang. Twin Co-Adaptive Dialogue for Progressive Image Generation. The 33rd ACM International Conference on Multimedia (ACM MM’25), Oct 27-31, 2025, Dublin, Ireland.
  3. Haotian Liu, Guo Yu, Hu Cao, Sanqing Qu, Fan Lu, Yan Zhong, Zhichao Lu, Luziwei Leng, Guang Chen. I2EKD: Efficient and Versatile Image-to-Event Knowledge Distillation. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2025.
  4. Yan Zhong, Chenxi Yang, Suyuan Zhao, Tingting Jiang. Semi-Supervised Blind Quality Assessment with Confidence-quantifiable Pseudo-label Learning for Authentic Images. The 42nd International Conference on Machine Learnin (ICML’25), July 13-19, 2025, Vancouver, Canada.
  5. Suyuan Zhao, Yizhen Luo, Ganbo Yang, Yan Zhong, Hao Zhou, Zaiqing Nie. SToFM: a Multi-scale Foundation Model for Spatial Transcriptomics. The 42nd International Conference on Machine Learnin (ICML’25), July 13-19, 2025, Vancouver, Canada.
  6. Yan Zhong, Xinping Zhao, Guangzhi Zhao, Bohua Chen, Fei Hao, Ruoyu Zhao, Jiaqi He, Lei Shi, Li Zhang. CTD-inpainting: Towards the coherence of text-driven inpainting with Blended Diffusion. Information Fusion, 103163, 2025.
  7. Wenbo Xu, Li Zhang, Yan Zhong, Haonan Jiang, Xue Wang, Rujing Wang, Liu Liu. Pre-defined Keypoints Promote Category-level Articulation Pose Estimation via Multi-Modal Alignment. The 34th International Joint Conference on Artificial Intelligence (IJCAI’25), August 16-22, 2025, Montreal, Canada.
  8. Shuaijie Shen, Chao Wang, Renzhuo Huang, Yan Zhong, Qinghai Guo, Zhichao Lu, Jianguo Zhang, Luziwei Leng. Spikingssms: Learning Long Sequences with Sparse and Parallel Spiking State Space Models. The 39th AAAI Conference on Artificial Intelligence (AAAI’25, Oral), February 25 - March 4, 2025, Philadelphia, Pennsylvania, USA.
  9. Li Zhang, Haonan Jiang, Yukang Huo, Yan Zhong, Jianan Wang, Xue Wang, Rujing Wang, Liu Liu. R$^2$-Art: Category-Level Articulation Pose Estimation from Single RGB Image via Cascade Render Strategy. The 39th AAAI Conference on Artificial Intelligence (AAAI’25), February 25 - March 4, 2025, Philadelphia, Pennsylvania, USA.
  10. Xiaoxi Sun, Jinpeng Li, Yan Zhong, Dongyan Zhao, Rui Yan. Towards Detecting LLMs Hallucination via Markov Chain-based Multi-agent Debate Framework.The ICASSP 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’25). April 06 - 11, 2025, Hyderabad, India; Suzhou, China.
  11. Li Zhang, Dong Li, Yan Zhong, Jiaying Zhu, Rujing Wang, Xingyu Wu, Xue Wang, Liu Liu. Rethinking Image Forgery Detection and Localization via Regression Perspective. IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), 2025.
  12. Xinping Zhao, Yan Zhong, Zetian Sun, Xinshuo Hu, Zhenyu Liu, Dongfang Li, Baotian Hu, Min Zhang. Funnelrag: A Coarse-to-Fine Progressive Retrieval Paradigm for RAG. The 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL’25), April 29–May 4, 2025, Albuquerque, New Mexico.
  13. Yan Zhong, Xingyu Wu, Xinping Zhao, Li Zhang, Xinyuan Song, Lei Shi, Bingbing Jiang. Semi-Supervised Multi-Label Feature Selection with Consistent Sparse Graph Learning. ArXiv preprint arXiv:2505.17875.
  14. Yukang Huo, Xianhui Meng, Li Zhang, Haonan Jiang, Yan Zhong, Mingyuan Yao, Haihua Wang. Diff-Art: Category-level Articulation Pose Estimation via Conditional Diffusion. IEEE International Conference on Multimedia & Expo 2025 (ICME’25), June 30 - July 4, 2025, Nantes, France.
  15. Li Zhang *, Yan Zhong *, Jianan Wang, Zhe Min, Rujing Wang, Liu Liu. Rethinking 3D Convolution in $l_p$-norm Space. The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS’24, Spotlight). Dec 10 - Dec 15,2024, Vancouver, Canada.
  16. Xinping Zhao, Dongfang Li, Yan Zhong, Boren Hu, Yibin Chen, Baotian Hu, Min Zhang. SEER: Self-Aligned Evidence Extraction for Retrieval-Augmented Generation. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP’24), Nov 12th - Nov 16th, 2024, Miami, Florida, USA.
  17. Shuhang Tan, Zhiling Wang, Yan Zhong. RCP‐RF: A Comprehensive Road‐car‐pedestrian Risk Management Framework Based on Driving Risk Potential Field. IET Intelligent Transport Systems, 18(12): 2618-2640. 2024.
  18. Yan Zhong *, Ruoyu Zhao *, Chao Wang, Qinghai Guo, Jianguo Zhang, Zhichao Lu, Luziwei Leng. SPikE-SSM: A Sparse, Precise, and Efficient Spiking State Space Model for Long Sequences Learning. ArXiv preprint arXiv:2410.17268, 2024.
  19. Li Zhang, Zean Han, Yan Zhong, Qiaojun Yu, Xingyu Wu, Xue Wang, Rujing Wang. Vocapter: Voting-based Pose Tracking for Category-level Articulated Object via Inter-frame Priors. Proceedings of the 32nd ACM International Conference on Multimedia (ACM MM’24), Oct 28 - Nov 1, 2024, Melbourne, Australia.
  20. Xingyu Wu, Yan Zhong, Jibin Wu, Yuxiao Huang, Sheng-hao Wu, Kay Chen Tan. Unlock the Power of Algorithm Features: A Generalization Analysis for Algorithm Selection. ArXiv preprint arXiv:2405.11349.
  21. Yunya Zhou, Bin Yuan, Yan Zhong#, Yuling Li#. Multi-label Robust Feature Selection via Subspace-Sparsity Learning. The 2024 International Conference on Artificial Neural Networks (ICANN’24), Sep 17 - 20, 2024, Viganello, Switzerland.
  22. Dongjie Yuan, Bin Yuan#, Yan Zhong#. Multi-label Feature Selection with Adaptive Subspace Learning. The 2024 International Conference on Knowledge Science, Engineering and Management (KSEM’24), August 16 - 18, 2024, Birmingham, UK.
  23. Zihao Xu, Chenglong Zhang, Zhaolong Ling, Peng Zhou, Yan Zhong, Li Li, Han Zhang, Weiguo Sheng, Bingbing Jiang. Multi-View Semi-Supervised Feature Selection with Graph Convolutional Networks. The 2024 International Joint Conference on Neural Networks (IJCNN’24). Jun 30 - Jul 5, 2024, Yokohama, Japan.
  24. Chenglong Zhang, Xinjie Zhu, Zidong Wang, Yan Zhong, Weiguo Sheng, Weiping Ding, Bingbing Jiang. Discriminative Multi-View Fusion Via Adaptive Regression. IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), 2024.
  25. Yan Zhong, Xingyu Wu, Li Zhang, Chenxi Yang, Tingting Jiang. Causal-IQA: Towards the Generalization of Image Quality Assessment Based on Causal Inference. The 41st International Conference on Machine Learnin (ICML’24), July 21 - 27, 2024, Vienna, Austria.
  26. Xingyu Wu, Yan Zhong, Zhaolong Ling, Jie Yang, Li Li, Weiguo Sheng, Bingbing Jiang. Nonlinear Learning Method for Local Causal Structures. Information Sciences, 654: 119789, 2024.
  27. Li Zhang, Weiqing Meng, Yan Zhong, Bin Kong, Mingliang Xu, Jianming Du, Xue Wang, Rujing Wang, Liu Liu. U-COPE: Taking a Further Step to Universal 9D Category-Level Object Pose Estimation. The 18th European Conference on Computer Vision (ECCV’24), Sep 29 - Oct 4, 2024, Milan, Italy.
  28. Xingyu Wu, Yan Zhong, Jibin Wu, Bingbing Jiang, Kay Chen Tan. Large Language Model-enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation. The 33rd International Joint Conference on Artificial Intelligence (IJCAI’24, Oral), August 03 -09, 2024, Jeju, Korea.
  29. Bingbing Jiang, Chenglong Zhang, Yan Zhong, Yi Liu, Yingwei Zhang, Xingyu Wu, Weiguo Sheng. Adaptive Collaborative Fusion for Multi-view Semi-supervised Classification. Information Fusion, vol 96 (8), pp. 37 - 50, 2023.
  30. Xingyu Wu, Bingbing Jiang, Yan Zhong, Huanhuan Chen. Multi-target Markov Boundary Discovery: Theory, Algorithm, and Application. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 4, pp. 4964 - 4980, 2023.
  31. Yan Zhong, Xingyu Wu, Bingbing Jiang, Huanhuan Chen. Multi-label Local-to-Global Feature Selection. International Joint Conference on Neural Networks (IJCNN’21), July 18–22, 2021, Virtual Event, Shenzhen, China.
  32. Xingyu Wu, Bingbing Jiang, Yan Zhong, Huanhuan Chen. Tolerant Markov Boundary Discovery for Feature Selection. The 29th ACM International Conference on Information and Knowledge Management (CIKM’20, Oral), October 19–23, 2020, Virtual Event, Ireland.
  33. Long Zhang, Chenge Wei, Wei Chang, Ruihang Zhang and Yan Zhong. Improvement of Newton Iteration Method in Constrained Optimization of Sketches. Electronic Science and Technology, 2018: 31(4), 64-67.

    Note: * denotes the co-first authors, and # indicates the corresponding author. Some papers are Under Review.

Issued Patents

  1. Yan Zhong, Wei Wang, Ruoyi Xu, Zhongqian Xie, Xinyan Zhao, Fangxin Wang and Shuhang Tan. Method, Device, Apparatus and Medium for Text Processing. (2022 Patent) (Patent Number: CN115292449A)
  2. Wei Wang, Yan Zhong, Liting Qian, Shandong Ye, Chao Chen and Huanhuan Chen. Method and System for Determining the Causal Relationship between BMD and Factors Affecting BMD. (2021 Patent) (Patent Number: CN112998653A)

Participated Books

  1. Multimodal Embeddings for Representation Learning.
  2. Exploring Multimodal Embeddings for Text and Impact on Language Processing.
  3. Mastering Reinforcement Learning: Foundations, Algorithms, and Real-World Applications.
  4. Advanced Deep Learning Methods for Protein Structure Prediction and Design.
  5. Ethics and Social Implications of Large Language Models.
  6. Deep Learning and Machine Learning: Contrastive Learning, from scratch to application.

Technical Reports and Benchmarks

  1. Kimi Team. Kimi-VL Technical Report. Code and Models.
  2. VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?. ArXiv preprint arXiv:2505.23359. Data. Code. Project.

🏆 Honors and Awards

  • The President’s Scholarship of Peking University (Top 5%), 2025.06.
  • Mathematics Graduate Award of Beijing International Center for Mathematical Research (BICMR), 2024.12.
  • Outstanding Research Award of Peking University, 2024.11.
  • The Zheng Geru Scholarship of Peking University, 2024.10.
  • ATEC 2023 Knowledge Introducing for LLM Contest (Rank Top 2), 2024.02.
  • The 2nd Prize of Huawei Software Elite Challenge (Rank Top 5), 2022.04.
  • The 3rd Prize in Huawei Cup Mathematical Modeling Contest (Top 15%), 2020.12.
  • The NWPU Excellent Student Honor (Top 5%), 2019.06.
  • The National Scholarship (Top 1%), 2018.10.
  • The $H$ Prize in the COMAP MCM/ICM (Top 15%), 2018.04.
  • The NWPU Self-improvement Scholarship (Top 15%), 2017.10.
  • The NWPU Special Scholarship of Yajun Wu (Top 3%), 2017.10.
  • The National Encouragement Scholarship (Top 5%), 2016.10.
  • Six consecutive years of the 1st Study Scholarship (Top 10%), 2016 - 2021.

📆 Academic Experiences and Internships

Algorithm Research Intern in Moonshot AI, Singapore. 2025.06 - 2025.09

  • Participated in the project of Kimi-VL and Kimi-VL-Thinking, which are the latest open source lightweight yet powerful Vision-Language Models with reasoning capability.

Algorithm Research Intern in ACS Lab, Huawei Technologies, Beijing, China. 2023.07 - 2025.04

  • Researched for the intelligent computing method based on SNNs and State Space Model (SSM).
  • Explored and Exploited the Bio-interpretable Dynamical Properties in SNN-Based SSMs for Long Sequence Learning.

Visiting Scholar in Southern University of Science and Technology, Shenzhen, China. 2022.06 - 2022.09

  • Research visit in the Evolving Machine Intelligence Group (EMI Lab), hosted by Ran Cheng.
  • Research for intelligent computing method based on SNNs and State Space Model (SSM).

Recommendation Algorithm Engineer Intern in NetEase, Hangzhou, China. 2022.01 - 2022.05

  • Participated in the Long Text Keyword Extraction and Fine-grained Named Entity Recognition projects in the NetEase Music Division.
  • Participated in the Heart Encounter Chat project, responsible for text analysis, conversation generation, NLP and other related business.
  • Participated in the CLUE Fine-grained NER competition and achieved (Top 10%).

Machine Learning Engineer Intern in SF Technology, Shenzhen, China. 2021.06 - 2021.09

  • Participated in the Address Standardization project and B-side Client Identification project.
  • Participated in the Vehicle Routing Optimization and Big Data Analysis projects.

Study in Zhejiang University, Hangzhou, China. 2018.07 - 2018.08.

  • Qiushi summer school in School of Mathematical Science.
  • Courses: Langlands Program, Geometric Theory of Partial Differential Equations, Computing Methods of Stochastic Differential Equations, etc.

📕 Teaching

  • 2022.09-2023.01: Worked as the teaching assistant (TA) for the Artificial Neural Networks class in Peking University, delivering lectures and support to both bachelor’s and master’s students.
  • 2023.02-2023.06: Worked as the teaching assistant (TA) for the Computer Graphics class in Peking University, delivering lectures and support to both bachelor’s and master’s students.
  • 2023.09-2024.01: Worked as the teaching assistant (TA) for the Higher Mathematics course in Peking University, delivering lectures and support to bachelor’s students.
  • 2024.02-2024.06: Worked as the teaching assistant (TA) for the Artificial Neural Networks class in Peking University, delivering lectures and support to both bachelor’s and master’s students.

⏳ Services

Program Committee Member (PC)

  • The 36th AAAI Conference on Artificial Intelligence (AAAI’22)
  • The 2023 International Joint Conference on Neural Networks (IJCNN’23)
  • The 38th AAAI Conference on Artificial Intelligence (AAAI’24)
  • The 2024 International Joint Conference on Neural Networks (IJCNN’24)
  • The 33rd International Joint Conference on Artificial Intelligence (IJCAI’24)
  • The 33rd ACM International Conference on Multimedia (ACM MM’24)
  • The 38th Annual Conference on Neural Information Processing Systems (NeurIPS’24)
  • The 13th International Conference on Learning Representations (ICLR’25)
  • The 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’25)
  • The 42nd International Conference on Machine Learning (ICML’25)
  • The 2025 International Conference on Computer Vision (ICCV’25)
  • The 34th ACM International Conference on Multimedia (ACM MM’25)
  • The 39th Annual Conference on Neural Information Processing Systems (NeurIPS’25)

Journal Invited Reviewer

  • IEEE Transactions on Knowledge and Data Engineering (TKDE, IEEE)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS, IEEE)
  • IEEE Transactions on Evolutionary Computation (TEVC, IEEE)
  • Information Fusion (INFFUS, Elsevier)
  • Information Processing and Management (IPM, Elsevier)
  • Engineering Applications of Artificial Intelligence (EAAI, Elsevier)
  • Complex & Intelligent Systems (CAIS, Springer)