I am a Ph.D. student in the College of Computer Science at Sichuan University, advised by Prof.Xi Peng.

My research mainly focuses on Multi-modal Learning, with contributions in:

• i) Robust Multi-modal Learning: I have worked extensively on tackling challenges such as modality missing (CVPR’21, TPAMI’22, AAAI’24-25) and noisy correspondence (ICCV’23, ICLR’24, NeurIPS’24) in image/video-text and image-image data. For a comprehensive overview of our work and insights on noisy correspondence, you can explore our repository Noisy Correspondence Summary.
• ii) Interactive Multi-modal Learning: I believe the future of multi-modal learning to center around interactions—between users, tools, and external knowledge. Some of my recent work is currently under review.
• iii) Bioinformatics: My work in this domain focuses on single-cell and multi-omics analysis, tackling key challenges such as representative cell selection (Nature Communications’25) and batch effect correction (TNNLS’23).

I am currently seeking postdoctoral opportunities. If you have any advice or are interested in exploring academic collaborations, please feel free to contact me. I look forward to your insights and suggestions.

🔥 News

• 2025.01:   One paper about AI4Science was accepted by Nature Communications!
• 2024.12:   One paper about diffusion clustering was accepted by AAAI Conference on Artificial Intelligence. Congrats to Yuanyang.
• 2024.06:   We completed a comprehensive survey on deep clustering from the prior perspective. 中文简介
• 2024.04:   One paper was accepted by IEEE Transactions on Systems, Man and Cybernetics: Systems.
• 2024.01:   One paper was accepted by International Conference on Learning Representations (ICLR 2024) as oral.
• 2023.12:   One paper was accepted by AAAI Conference on Artificial Intelligence (AAAI 2024). Congrats to Yiding.
• 2022.08:   One paper was accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).

📝 Publications

[ICLR’24] Multi-granularity Correspondence Learning from Long-term Noisy Videos
Yijie Lin, Jie Zhang, Zhenyu Huang, Jia Liu, Zujie Wen, Xi Peng

(Oral presentation, 1.2%) | 中文简介 | Slides | Poster | Project

• Reveal multi-granularity noisy correspondence problem in long-term temporal modeling.

• Propose an efficient and robust video-language pre-training method.

[CVPR’21] COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction
Yijie Lin, Yuanbiao Gou, Zitao Liu, Boyun Li, Jiancheng Lv, Xi Peng

Video | 中文简介 | Code

[TPAMI’22] Dual Contrastive Prediction for Incomplete Multi-view Representation Learning
Yijie Lin, Yuanbiao Gou, Xiaotian Liu, Jinfeng Bai, Jiancheng Lv, Xi Peng

中文简介 | Code

[ICCV’23] Graph Matching with Bi-level Noisy Correspondence
Yijie Lin, Mouxing Yang, Jun Yu, Peng Hu, Changqing Zhang, Xi Peng

Video | 中文简介 | Code

• Reveal bi-level (node- and edge-level) noisy correspondence challenge.
• This work is included by famous open-source graph matching project ThinkMatch

• [Nature Communications’25] MetaQ: fast, scalable and accurate metacell inference via single-cell quantization, Yunfan Li, Hancong Li, Yijie Lin, Dan Zhang, Dezhong Peng, Xiting Liu, Jie Xie, Peng Hu, Lu Chen, Han Luo, Xi Peng | Code

• [AAAI’25] Incomplete Multi-view Clustering via Diffusion Contrastive Generation, Yuanyang Zhang*, Yijie Lin*, Weiqing Yan, Li Yao, Xinhang Wan, Guangyuan Li, Chao Zhang, Guanzhou Ke, Jie Xu

• [NeurIPS’24] Robust Contrastive Multi-view Clustering against Dual Noisy Correspondence, Ruiming Guo, Mouxing Yang, Yijie Lin, Xi Peng, Peng Hu | Code

• [AAAI’24] Decoupled Contrastive Multi-view Clustering with High-order Random Walks, Yiding Lu, Yijie Lin, Mouxing Yang, Dezhong Peng, Peng Hu, Xi Peng | Code

• [Vicinagearth’24] A survey on deep clustering: from the prior perspective, Yiding Lu, Haobin Li, Yunfan Li, Yijie Lin, Xi Peng | 中文简介

• [TSMC’24] UNITE: Multitask Learning With Sufficient Feature for Dense Prediction, Yuxin Tian, Yijie Lin, Qing Ye, Jian Wang, Xi Peng, Jiancheng Lv | Code

• [TNNLS’23] Single-cell RNA-seq Debiased Clustering via Batch Effect Disentanglement, Yunfan Li, Yijie Lin, Han Luo, Peng Hu, Dezhong Peng, Xi Peng | Code

• [EMNLP Findings’22] Improve Interpretability of Neural Networks via Sparse Contrastive Coding, Junhong Liu*, Yijie Lin*, Liang Jiang, Jia Liu, Zujie Wen, Xi Peng

• [TIP’22] Unsupervised Neural Rendering for Image Hazing, Boyun Li, Yijie Lin, Xiao Liu, Peng Hu, Jiancheng Lv, Xi Peng

🎖 Honors and Awards

• 2024.12 Tencent Scholarship (Outstanding award at SCU)
• 2023.10 National Scholarship (PhD student)
• 2022.11 Huawei Scholarship (First prize at SCU)
  
• 2019.09 National Scholarship (Undergraduate, Top 1%)

🙋 Service

• Journal Reviewer: IEEE TIP, IEEE TKDE, IEEE TNNLS, IEEE TAI, and more.

• Conference Reviewer: ICLR, NeurIPS, ICML, CVPR, ICCV, ECCV, ACL, AAAI, ACMMM, and more.