Enneng Yang

Enneng Yang

Fourth-year Ph.D. Student

👋 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 had the privilege of working closely with Assoc. Prof. Li Shen and Dr. Zhenyi Wang. 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

  • 2024.09: Our paper about continual learning is accepted to TPAMI 2024.
  • 2024.07: Our paper about sequential recommendation is accepted to RecSys 2024.
  • 2024.06: Our paper about deconfounding recommendation is accepted to ACM TKDD 2024.
  • 2024.05: Our paper about model merging is accepted to ICML 2024.
  • 2024.02: Our paper about multi-task recommendation is accepted to ACM TKDD 2024.
  • 2024.01: Our paper about model merging is accepted to ICLR 2024.
  • 2023.10: Our paper about explanation recommendation is accepted to KBS 2023.
  • 2023.10: Our paper about sequential recommendation is accepted to TKDE 2023.
  • 2023.09: Our paper about dataset condensation is accepted to NeurIPS 2023.
  • 2023.07: Our paper about flatness-aware continual learning is accepted to ICCV 2023.
  • 2023.04: Our paper about next-basket recommendation is accepted to IJCAI 2023.

✨ Repositories

Comments and contributions are welcome. 👏

📝 Selected Preprints and Publications

$^{\ast}$ indicates equal contribution, $^{\dagger}$ indicates corresponding author

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.

  • A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
    Arxiv 2023 | Paper Code
    Zhenyi Wang, Enneng Yang, Li Shen, Heng Huang.

Conference Papers

  • 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 $^{\ast}$, 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 $^{\dagger}$, Li Shen $^{\dagger}$, Xiaochun Yang, Xiaodong He.

Journal Papers

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

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

📖 Educations

💻 Internships

🏆 Honors and Awards

  • 2023: National Scholarship (Top 1%)
  • 2020: Tencent Rhino-Bird Elite Talent Training Program (51 People Worldwide)
  • 2019: National Scholarship (Top 1%)
  • 2017: National Scholarship (Top 1%)

💬 Invited Talks

  • 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 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
  • The Web Conference (International World Wide Web Conference) (WWW) 2023
  • ACM International Conference on Web Search and Data Mining (WSDM) 2023

Journal Reviewers

  • 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