👋 About Me

Hello! This is Enneng Yang. I’m currently a Postdoc Researcher at Shenzhen Campus of Sun Yat-sen University, China, advised by Assoc. Prof. Li Shen. Before that, I received the PhD degree (June 2025) from Northeastern University, China, advised by Prof. Guibing Guo. 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 large language models, machine learning, and recommender systems. More specifically, I focus on:

• Large Language Model: continual pretraining/finetuning, knowledge editing
• Machine Learning: model merging, multi-task learning, continual/incremental learning, data-free learning, dataset/knowledge distillation
• Recommendation System: multi-task/multi-scenario recommendation, sequential recommendation, OOD recommendation

🔥 News

• 2025.09: Our two papers about continual model merging are accepted to NeurIPS 2025.
• 2025.05: Our one paper about knowledge editing is accepted to ACL (main) 2025.
• 2025.05: Our one paper about model merging is accepted to ICML 2025.
• 2025.04: Our one paper about explainable recommendations is accepted to TOIS 2025.
• 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.

• Awesome-Model-Merging-Methods-Theories-Applications
  This repository collects the latest research on Model Merging in Machine Learning.
• Awesome-Forgetting-in-Deep-Learning
  This repository collects the latest research on Catastrophic Forgetting in Deep Learning.
• FusionBench
  This repository integrates the latest model merging algorithm.

📝 Selected Preprints and Publications

Survey or Benchmark Papers

• Unifying Multimodal Large Language Model Capabilities and Modalities via Model Merging
  Arxiv 2025 | Code
  Yongxian Wei, Runxi Cheng, Weike Jin, Enneng Yang, Li Shen, Lu Hou, Sinan Du, Chun Yuan, Xiaochun Cao, Dacheng Tao.

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

• Data Augmentation for Sequential Recommendation: A Survey
  Arxiv 2024 | 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 | Code
  Zhenyi Wang, Enneng Yang, Li Shen, Heng Huang.

Conference Papers

• Continual Model Merging without Data: Dual Projections for Balancing Stability and Plasticity
  NeurIPS 2025 | Code
  Enneng Yang, Anke Tang, Li Shen, Guibing Guo, Xingwei Wang, Xiaochun Cao, Jie Zhang.

• Merging on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging
  NeurIPS 2025 | Code
  Anke Tang, Enneng Yang, Li Shen, Yong Luo, Han Hu, Lefei Zhang, Bo Du, Dacheng Tao.

• Knowledge Decoupling via Orthogonal Projection for Lifelong Editing of Large Language Models
  ACL 2025
  Haoyu Xu, Pengxiang Lan, Enneng Yang, Guibing Guo, Jianzhe Zhao, Linying Jiang, Xingwei Wang.

• Representation Surgery in Model Merging with Probabilistic Modeling
  ICML 2025 | Code
  Qi Wei, Shuo He, Enneng Yang, Tingcong Liu, Haobo Wang, Lei Feng, Bo An.

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

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

• Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model
  WWW 2025 | 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) | 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) | 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) | 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 | 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 | 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 | Code
  Enneng Yang, Li Shen, Zhenyi Wang, Tongliang Liu, Guibing Guo.

• Data Augmented Flatness-aware Gradient Projection for Continual Learning
  ICCV 2023 | 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) | 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)
  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) | 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)| Code
  Guibing Guo, Enneng Yang$^{\dagger}$ ($^{\dagger}$ indicates corresponding authors), Li Shen$^{\dagger}$, Xiaochun Yang, Xiaodong He.

Journal Papers

• Preference Logical Reasoning with Preference Operators for Explainable Recommendations
  TOIS 2025 | Code
  Fei Li, Enneng Yang, Guibing Guo, Linying Jiang, Jianzhe Zhao, and Xingwei Wang.

• Symmetric Graph Contrastive Learning against Noisy Views for Recommendation
  TOIS 2025 | 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 | 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
  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 | 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 | Code
  Yizhou Dang, Enneng Yang, Guibing Guo, Linying Jiang, Xingwei Wang, Xiaoxiao Xu, Qinghui Sun, Hong Liu.

📖 Educations

• 2024.03 - 2025.03: Visiting Ph.D. Student at Nanyang Technological University, Singapore.
• 2021.09 - 2025.06: Ph.D. Student at Northeastern University, China.

💻 Internships

• 2023.05 - 2023.09: Intern at Digital China Group Co., Ltd.
• 2022.01 - 2022.06: Research Intern at Tencent Inc, mentored by Junwei Pan.
• 2020.05 - 2021.02: Research Intern at Tencent Inc, mentored by Junwei Pan and Dr. Xiaoqing Cao.

🏆 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%)

🔖 Services

• Conference Reviewers: CVPR 2026, ICLR 2026, AAAI 2026, NeurIPS 2025, ICCV 2025, ICML 2025, WWW 2025, ICLR 2025, AAAI 2025, NeurIPS 2024, ICML 2024, KDD 2024, AAAI 2024, WWW 2023, WSDM 2023
• Journal Reviewers: TMLR 2024, TSC 2024, TBD 2024, TCSVT 2024, NCAA 2024, TORS 2022