Bio

I am a first-year Ph.D. student in Computer Science at Rutgers University, working with Prof. Yongfeng Zhang. Currently, I am an Applied Scientist Intern at Amazon. My research interests include graph machine learning, recommender systems, and large language models and agents.

Feel free to contact me if you would like to learn more about me, and check out my CV here (July 2025).

Publications

LLM and LLM Agents

• DeQA: Decentralized Agentic Question Answering with Tokenomics.
  Xi Zhu, Zhuoqiao Shen, Jingyuan Huang, Kai Mei, Shuhang Lin, Minghao Guo, Yongfeng Zhang.

• LiteCUA: Computer as MCP Server for Computer-Use Agent on AIOS.
  Kai Mei, Xi Zhu, Hang Gao, Shuhang Lin, Yongfeng Zhang.
  arXiv:2505.18829. [Link] [Code]

• AIOS: LLM Agent Operating System.
  Kai Mei, Xi Zhu, Wujiang Xu, Wenyue Hua, Mingyu Jin, Zelong Li, Shuyuan Xu, Ruosong Ye, Yingqiang Ge, Yongfeng Zhang.
  In Proceedings of the 2nd Conference on Language Modeling (COLM 2025), 2025. [Link] [Code]

• Recommender Systems Meet Large Language Model Agents: A Survey.
  Xi Zhu*, Yu Wang*, Hang Gao*, Wujiang Xu*, Chen Wang, Zhiwei Liu, Kun Wang, Mingyu Jin, Linsey Pang, Qingsong Wen, Philips S. Yu, Yongfeng Zhang.
  In Foundations and Trends in Privacy and Security, 2025. [Link]

• iAgent: LLM Agent as a Shield between User and Recommender Systems.
  Wujiang Xu, Yunxiao Shi, Zujie Liang, Xuying Ning, Kai Mei, Kun Wang, Xi Zhu, Min Xu, Yongfeng Zhang.
  In Findings of the 63th Annual Meeting of the Association for Computational Linguistics (ACL 2025), 2025. [Link] [Code]

Graph Machine Learning

• LLM as GNN: Graph Vocabulary Learning for Text-attributed Graph Foundation Model.
  Xi Zhu*, Haochen Xue*, Ziwei Zhao, Wujiang Xu, Jingyuan Huang, Minghao Guo, Qifan Wang, Kaixiong Zhou, Yongfeng Zhang.
  arXiv: 2503.03313 [Link] [Code]

• Adversarial Attack and Defense on Discrete Time Dynamic Graphs.
  Ziwei Zhao, Yu Yang, Zikai Yin, Tong Xu, Xi Zhu, Fake Lin, Xueying Li, Enhong Chen.
  In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2024. [Link]

• Few-shot Link Prediction for Event-based Social Networks via Meta-learning.
  Xi Zhu, Pengfei Luo, Ziwei Zhao, Tong Xu, Aakas Lizhiyu, Yu Yu, Xueying Li, Enhong Chen.
  In Proceedings of the 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), 2023. [Link] [Code] [Competition]

• Semantic Interaction Matching Network for Few-shot Knowledge Graph Completion.
  Pengfei Luo, Xi Zhu, Tong Xu, Yi Zheng, Enhong Chen.
  In ACM Transactions on the Web (ACM TWEB), 2022. [Link] [Code]

Recommender Systems

• Multi-Behavior Recommendation with Personalized Directed Acyclic Behavior Graphs.
  Xi Zhu, Fake Lin, Ziwei Zhao, Tong Xu, Xiangyu Zhao, Zikai Yin, Xueying Li, Enhong Chen.
  In ACM Transactions on Information Systems (ACM TOIS), 2024. [Link] [Code]

• When Box Meets Graph Convolutional Network in Tag-aware Recommendation.
  Fake Lin, Ziwei Zhao, Xi Zhu, Da Zhang, Shitian Shen, Xueying Li, Tong Xu, Suojuan Zhang, Enhong Chen.
  In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024),2024. [Link] [Code]

• Knowledge Graph Pruning for Recommendation.
  Fake Lin, Xi Zhu, Ziwei Zhao, Deqiang Huang, Yu Yu, Xueying Li, Tong Xu, Enhong Chen.
  arXiv:2405.11531. [Link]

• DynLLM: When Large Language Models meet Dynamic Graph Recommendation.
  Ziwei Zhao, Fake Lin, Xi Zhu, Zhi Zheng, Tong Xu, Shitian Shen, Xueying Li, Zikai Yin, Enhong Chen.
  arXiv:2405.07580. [Link]

• Time-interval Aware Share Recommendation via Bi-directional Continuous Time Dynamic Graphs.
  Ziwei Zhao, Xi Zhu, Tong Xu, Aakas Lizhiyu, Yu Yu, Xueying Li, Zikai Yin, Enhong Chen.
  In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023), 2023. [Link] [Code]

• H3GNN: Hybrid Hierarchical HyperGraph Neural Network for Personalized Session-based Recommendation.
  Zhizhuo Yin, Kai Han, Pengzi Wang, Xi Zhu.
  In ACM Transactions on Information Systems (ACM TOIS), 2023. [Link]

Education

• Ph.D. Student, 2024 - present, Rutgers University, New Brunswick, NJ.
  Major: Computer Science
  Advisor: Prof. Yongfeng Zhang

• M.E. Student, 2020 - 2023, University of Science and Technology of China (USTC), Hefei, China.
  Major: Computer Science (Data Science)
  Advisors: Prof. En-Hong Chen (IEEE Fellow) and Prof. Tong Xu
  Affiliation: State Key Laboratory of Cognitive Intelligence

• B.E. Student, 2016 - 2020, Sichuan University (SCU), Chengdu, China.
  Major: Computer Science

Internship Experiences

• Applied Scientist Intern, Amazon, Seattle, WA, May 2025 - present

• Research Intern, Alibaba, Hangzhou, China, Dec 2021 - Nov 2023

Teaching Experiences

• Teaching Assistant, CS527: Database System for Data Science, Rutgers University, 2025 Spring

• Teaching Assistant, CS439: Introduction to Data Science, Rutgers University, 2024 Fall

• Teaching Assistant, 11179.01: Web Information Processing and Application, University of Science and Technology of China, 2021 Fall

Academic Service

• Reviewer: ACM TOIS, IEEE TKDE, IEEE TNNLS
• PC Member: RecSys 2024/2025, WWW 2025, KDD 2025/2026, NeurIPS 2025

Honors and Awards

• National Scholarship, Dec 2019
• Outstanding Undergraduate, Jun 2020
• Meritorious Winner of Mathematical Contest in Modeling (MCM), COMAP, Apr 2019
• First-class Freshman Academic Scholarship of USTC, 2020
• First-class Comprehensive Scholarship of SCU, 2019
• Second-class Comprehensive Scholarship of SCU (two times), 2017, 2018
• Third Prize, National Undergraduate Mathematics Competition of China, Dec 2017