Enneng Yang

Enneng Yang

Fourth-year Ph.D. Student

👋 About Me

Hello! This is Enneng Yang. I’m currently a fourth-year Ph.D. student in Software College, Northeastern University, China, advised by Prof. Guibing Guo. I am honored to work closely with Assoc. Prof. Li Shen of Sun Yat-sen University, China. From March 2024 to March 2025, I am a visiting Ph.D. student in Prof. Jie Zhang’s group at Nanyang Technological University, Singapore.

My research interests lie in machine learning and recommender system. More specifically, I focus on:

  • Machine Learning: foundation models, model merging, multi-task learning, continual/incremental learning, data-free learning, dataset/knowledge distillation
  • Recommendation System: multi-task/multi-scenario recommendation, sequential recommendation, robust recommendation, CTR/CVR prediction, discrete recommendation

🔥 News

  • 2025.04: Our two papers about sequential recommendations are accepted to SIGIR 2025.
  • 2025.02: Our one paper about out-of-distribution recommendation is accepted to TOIS 2025.
  • 2025.01: Our one paper about flatness-aware continual learning is accepted to TPAMI 2025.
  • 2025.01: Our two papers about out-of-distribution recommendations are accepted to WWW 2025.
  • 2024.12: Our two papers about LLMs fine-tuning and sequential recommendation are accepted to AAAI 2025.
  • 2024.11: Our one paper about recommendation unlearning is accepted to TOIS 2024.
  • 2024.11: Our one survey paper about forgetting in deep learning is accepted to TPAMI 2024.
  • 2024.09: Our one paper about continual learning is accepted to TPAMI 2024.
  • 2024.05: Our one paper about model merging is accepted to ICML 2024.
  • 2024.01: Our one paper about model merging is accepted to ICLR 2024.
  • 2023.10: Our one paper about sequential recommendation is accepted to TKDE 2023.
  • 2023.09: Our one paper about dataset condensation is accepted to NeurIPS 2023.
  • 2023.07: Our one paper about flatness-aware continual learning is accepted to ICCV 2023.
  • 2023.04: Our one paper about next-basket recommendation is accepted to IJCAI 2023.

    • More

✨ Repositories

Comments and contributions are welcome.

📝 Selected Preprints and Publications

Survey Papers

  • Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities
    Arxiv 2024 | Paper Code
    Enneng Yang, Li Shen, Guibing Guo, Xingwei Wang, Xiaochun Cao, Jie Zhang, Dacheng Tao.

  • Data Augmentation for Sequential Recommendation: A Survey
    Arxiv 2024 | Paper Code
    Yizhou Dang, Enneng Yang, Yuting Liu, Guibing Guo, Linying Jiang, Jianzhe Zhao, Xingwei Wang.

  • A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
    TPAMI 2024 | Paper Code
    Zhenyi Wang, Enneng Yang, Li Shen, Heng Huang.

Conference Papers

  • Data Augmentation as Free Lunch: Exploring the Test-Time Augmentation for Sequential Recommendation
    SIGIR 2025 | Paper Code
    Yizhou Dang, Yuting Liu, Enneng Yang, Minhan Huang, Guibing Guo, Jianzhe Zhao and Xingwei Wang.

  • Denoising Multi-Interest-Aware Logical Reasoning for Long-Sequence Recommendation
    SIGIR 2025 | Just Accepted Code
    Fei Li, Qingyun Gao, Yizhou Dang, Enneng Yang, Guibing Guo, Jianzhe Zhao and Xingwei Wang.

  • Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model
    WWW 2025 | Paper Code
    Chu Zhao, Enneng Yang, Yuliang Liang, Jianzhe Zhao, Guibing Guo, Xingwei Wang.

  • Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendation
    WWW 2025 (Oral) | Paper Code
    Chu Zhao, Enneng Yang, Yuliang Liang, Pengxiang Lan, Yuting Liu, Jianzhe Zhao, Guibing Guo, Xingwei Wang.

  • Efficient Prompt Tuning by Multi-Space Projection and Prompt Fusion
    AAAI 2025 (Oral) | Paper Appendix
    Pengxiang Lan, Enneng Yang, Yuting Liu, Guibing Guo, Linying Jiang, Jianzhe Zhao, Xingwei Wang.

  • Augmenting Sequential Recommendation with Balanced Relevance and Diversity
    AAAI 2025 (Oral) | Paper Appendix Code
    Yizhou Dang, Jiahui Zhang, Yuting Liu, Enneng Yang, Yuliang Liang, Guibing Guo, Jianzhe Zhao, Xingwei Wang.

  • Representation Surgery for Multi-Task Model Merging
    ICML 2024 | Paper Code
    Enneng Yang, Li Shen, Zhenyi Wang, Guibing Guo, Xiaojun Chen, Xingwei Wang, Dacheng Tao.

  • AdaMerging: Adaptive Model Merging for Multi-Task Learning
    ICLR 2024 | Paper Code
    Enneng Yang, Zhenyi Wang, Li Shen, Shiwei Liu, Guibing Guo, Xingwei Wang, Dacheng Tao.

  • An Efficient Dataset Condensation Plugin and Its Application to Continual Learning
    NeurIPS 2023 | Paper Code
    Enneng Yang, Li Shen, Zhenyi Wang, Tongliang Liu, Guibing Guo.

  • Data Augmented Flatness-aware Gradient Projection for Continual Learning
    ICCV 2023 | Paper Appendix Code
    Enneng Yang, Li Shen, Zhenyi Wang, Shiwei Liu, Guibing Guo, Xingwei Wang.

  • AdaTask: A Task-aware Adaptive Learning Rate Approach to Multi-task Learning
    AAAI 2023 (Oral) | Paper Appendix Code
    Enneng Yang, Junwei Pan, Ximei Wang, Haibin Yu, Li Shen, Xihua Chen, Lei Xiao, Jie Jiang, Guibing Guo.

  • Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation
    IJCAI 2023 (Oral) | Paper
    Yalin Yu$^{\ast}$, Enneng Yang$^{\ast}$ ($^{\ast}$ indicates co-first authors), Guibing Guo, Linying Jiang, Xingwei Wang.

  • Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation
    AAAI 2023 (Oral) | Paper Code
    Yizhou Dang, Enneng Yang, Guibing Guo, Linying Jiang, Xingwei Wang, Xiaoxiao Xu, Qinghui Sun, Hong Liu.

  • Discrete Trust-aware Matrix Factorization for Fast Recommendation
    IJCAI 2019 (Oral) | Paper Code
    Guibing Guo, Enneng Yang$^{\dagger}$ ($^{\dagger}$ indicates corresponding authors), Li Shen$^{\dagger}$, Xiaochun Yang, Xiaodong He.

Journal Papers

  • Symmetric Graph Contrastive Learning against Noisy Views for Recommendation
    TOIS 2025 | Paper Code
    Chu Zhao, Enneng Yang, Yuliang Liang, Jianzhe Zhao, Guibing Guo, and Xingwei Wang.

  • Revisiting Flatness-aware Optimization in Continual Learning with Orthogonal Gradient Projection
    TPAMI 2025 | Paper Code
    Enneng Yang, Li Shen, Zhenyi Wang, Shiwei Liu, Guibing Guo, Xingwei Wang, and Dacheng Tao.

  • Continual Learning From a Stream of APIs
    TPAMI 2024 | Paper
    Enneng Yang, Zhenyi Wang, Li Shen, Nan Yin, Tongliang Liu, Guibing Guo, Xingwei Wang, Dacheng Tao.

  • Efficient and Adaptive Recommendation Unlearning: A Guided Filtering Framework to Erase Outdated Preferences
    TOIS 2024 | Paper Code
    Yizhou Dang, Yuting Liu, Enneng Yang, Guibing Guo, Linying Jiang, Jianzhe Zhao, Xingwei Wang.

  • TiCoSeRec: Augmenting Data to Uniform Sequences by Time Intervals for Effective Recommendation
    TKDE 2023 | Paper Code
    Yizhou Dang, Enneng Yang, Guibing Guo, Linying Jiang, Xingwei Wang, Xiaoxiao Xu, Qinghui Sun, Hong Liu.

📖 Educations

💻 Internships

🏆 Honors and Awards

  • 2025.01: Youth Talents Support Project - Doctoral Student Special Program (First Session)
  • 2024.10: National Scholarship (Top 1%)
  • 2023.10: National Scholarship (Top 1%)
  • 2020.05: Tencent Rhino-Bird Elite Talent Training Program (51 People Worldwide)
  • 2019.10: National Scholarship (Top 1%)
  • 2017.10: National Scholarship (Top 1%)

💬 Invited Talks

  • 2025.01: “Model Merging for Multi-task Learning”; Inviter: CCF·Shenzhen University
  • 2024.07: “Representation Surgery for Multi-task Model Merging”; Inviter: Wiztalk ICML 2024 Paper Sharing
  • 2021.05: “Opportunities and Challenges of Data Sparsity in Recommender Systems”; Inviter: CCF·YEF·2021

🔖 Services

Conference Reviewers

  • International Conference on Computer Vision (ICCV) 2025
  • Conference on Neural Information Processing Systems (NeurIPS) 2025
  • International Conference on Machine Learning (ICML) 2025
  • International World Wide Web Conference (WWW) 2025
  • International Conference on Learning Representations (ICLR) 2025
  • AAAI Conference on Artificial Intelligence (AAAI) 2025
  • Conference on Neural Information Processing Systems (NeurIPS) 2024
  • International Conference on Machine Learning (ICML) 2024
  • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2024
  • AAAI Conference on Artificial Intelligence (AAAI) 2024
  • International World Wide Web Conference (WWW) 2023
  • ACM International Conference on Web Search and Data Mining (WSDM) 2023

Journal Reviewers

  • Transactions on Machine Learning Research (TMLR) 2024
  • IEEE Transactions on Services Computing (TSC) 2024
  • IEEE Transactions on Big Data (TBD) 2024
  • IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) 2024
  • Neural Computing and Applications (NCAA) 2024
  • ACM Transactions on Recommender Systems (TORS) 2022