I am a 4th-year Ph.D. student in Computer Science at University of Illinois Urbana-Champaign, fortunately advised by Prof. Jiawei Han. Before that, I was an undergraduate student in Electrical Engineering of Tsinghua University, fortunately advised by Prof. Yong Li. During the past, I spent time at Google, Amazon Search, and Microsoft Research (both Redmond and Beijing).

My research is supported by Apple PhD Fellowship and Yunni and Maxine Pao Memorial Fellowship. For further information, please see my CV (last update: 2024.5.6).

Research Interests: My main research lies at the intersection of large generative models (e.g., large language models and diffusion models), multimodal data and information networks. In particular, I focus on how large models can integrate text, network, and multimodal data for solving real world problems including information retrieval and knowledge discovery. My current research interest is LLM alignment and RLHF.

• Large Generative Models + Graphs (Survey): representation learning (Heterformer, Edgeformers), pretraining (Patton), graph plug-in (Graph-CoT) and multimodal synthesis (InstructG2I).
• Large Generative Models + IR: RAG and long-context LLM (LongRAG), semantic indexer (LMIndexer), generative retrieval (RIPOR) and generative recommendation (UniMP).
• Large Generative Models + Science (Survey): general science (MAPLE, ToTER), geospatial science (GeoWise), climate science (CoDiCast) and healthcare (RAM-EHR).

I am maintaining awesome github repos on Large Language Models on Graphs and Multimodal Learning on Graphs with a survey paper. Feel free to have a look!

If you’re interested in my research or would like to discuss relevant topics and potential collaborations, feel free to reach out via email (bowenj4[AT]illinois.edu)! I also welcome inquiries from both master’s and undergraduate students, especially those from underrepresented groups. Looking forward to connecting!

News

• [2024.10] Gave a talk at Emory about multimodal learning on graphs!
• [2024.9] One paper on image synthesis on multimodal graphs has been accepted by NeurIPs 2024!
• [2024.9] Two papers on scientific LLMs and LLMs for RE have been accepted by EMNLP 2024!

Selected Publications [Full List]

(* denotes equal contribution)

Preprints

• Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG
  Bowen Jin, Jinsung Yoon, Jiawei Han, Sercan O. Arik.
  preprint 2024.
  [PDF] [Code]

Surveys

• Large Language Models on Graphs: A Comprehensive Survey
  Bowen Jin*, Gang Liu*, Chi Han*, Meng Jiang, Heng Ji, Jiawei Han.
  Transactions on Knowledge and Data Engineering (TKDE) 2024.
  [PDF] [Repo] 700+ stars

2025

• Improving Scientific Document Retrieval with Concept Coverage-based Query Set Generation
  SeongKu Kang, Bowen Jin, Wonbin Kweon, Yu Zhang, Dongha Lee, Jiawei Han, Hwanjo Yu.
  WSDM 2025.
  [PDF] [Code]

2024

• InstructG2I: Synthesizing Images from Multimodal Attributed Graphs
  Bowen Jin, Ziqi Pang, Bingjun Guo, Yu-Xiong Wang, Jiaxuan You, Jiawei Han.
  NeurIPs 2024.
  [PDF] [Code] [Model] [Project Page] [Media Coverage]

• Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs
  Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Suhang Wang, Yu Meng, Jiawei Han.
  ACL 2024 (findings).
  [PDF] [Code] [Data]

• Language Models as Semantic Indexers
  Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, et al.
  ICML 2024.
  [PDF] [Code]

• Investigating Instruction Tuning Large Language Models on Graphs
  Kerui Zhu*, Bo-Wei Huang*, Bowen Jin*, Yizhu Jiao, Ming Zhong, Kevin Chang, Shou-De Lin, Jiawei Han.
  COLM 2024.
  [PDF] [Code]

• A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery
  Yu Zhang*, Xiusi Chen*, Bowen Jin*, Sheng Wang, Shuiwang Ji, Wei Wang, Jiawei Han.
  EMNLP 2024.
  [PDF] [Repo]

• Grasping the Essentials: Tailoring Large Language Models for Zero-Shot Relation Extraction
  Sizhe Zhou, Yu Meng, Bowen Jin, Jiawei Han.
  EMNLP 2024.
  [PDF] [Code]

• Scalable and Effective Generative Information Retrieval
  Hansi Zeng, Chen Luo, Bowen Jin, Sheikh Muhammad Sarwar, Tianxin Wei, Hamed Zamani.
  WWW 2024.
  [PDF] [Code]

• Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy
  SeongKu Kang, Shivam Agarwal, Bowen Jin, Dongha Lee, Hwanjo Yu, Jiawei Han.
  WWW 2024.
  [PDF] [Code]

• Towards Universal Multi-Modal Personalization: A Language Model Empowered Generative Paradigm
  Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, et al.
  ICLR 2024.
  [PDF] [Code]

• Bridging Text Data and Graph Data: Towards Semantics and Structure-aware Knowledge Discovery
  Bowen Jin, Yu Zhang, Sha Li, Jiawei Han.
  WSDM 2024 (Tutorial).
  [PDF] [Tutorial Page]

2023

• Learning Multiplex Representations on Text-Attributed Graphs with One Language Model Encoder
  Bowen Jin, Wentao Zhang, Yu Zhang, Yu Meng, Han Zhao, Jiawei Han.
  NeurIPs 2023 (GLFrontiers).
  [PDF] [Code]

• Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks
  Bowen Jin, Yu Zhang, Qi Zhu, Jiawei Han.
  KDD 2023.
  [PDF] [Code]

• Patton: Language Model Pretraining on Text-rich Networks
  Bowen Jin, Wentao Zhang, Yu Zhang, Yu Meng, Xinyang Zhang, Qi Zhu, Jiawei Han.
  ACL 2023 (Oral).
  [PDF] [Code]

• Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
  Bowen Jin, Yu Zhang, Yu Meng, Jiawei Han.
  ICLR 2023 (Poster).
  [PDF] [Code]

• Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers
  Yu Zhang, Bowen Jin, Xiusi Chen, Yanzhen Shen, Yunyi Zhang, Yu Meng, Jiawei Han.
  KDD 2023.
  [PDF] [Code]

• Text Augmented Open Knowledge Graph Completion via Pre-Trained Language Models
  Pengcheng Jiang, Shivam Agarwal, Bowen Jin, Xuan Wang, Jimeng Sun, Jiawei Han
  ACL 2023 (findings).
  [PDF] [Code]

• The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study
  Yu Zhang, Bowen Jin, Qi Zhu, Yu Meng, Jiawei Han.
  WWW 2023.
  [PDF] [Code]

Before Ph.D.

• Multi-behavior Recommendation with Graph Convolutional Networks
  Bowen Jin, Chen Gao, Xiangnan He, Depeng Jin, Yong Li.
  SIGIR 2020.
  [PDF] [Code]

Education

• University of Illinois Urbana-Champaign, Ph.D. in Computer Science (2021 - Present).
• Tsinghua University, B.S. in Electrical Engineering and Statistics (2017 - 2021).

Professional Experience

• Google Cloud Research - Student Researcher
  2024.05-now
• Amazon Search - Applied Scientist Intern
  2023.05-2023.12
• Microsoft Research - Research Intern
  2022.05-2022.09
• Microsoft Research (Asia) - Research Intern
  2020.09-2021.3

Professional Service

• Reviewer: WSDM 2023, KDD 2023, NeurIPs 2023, ICLR 2024, WWW 2024, SDM 2024, ACL 2024, ICML 2024, COLM 2024, NeurIPs 2024

• Journal Reviewer: TKDE, TOIS, TBD

• Guest Instructor: UIUC Fall23 CS512

• Lead TA: UIUC Spring24 CS412

Talks

• [2024.10] Multimodal learning on graphs at Emory.

Miscellaneous

I started to play a traditional Chinese instrument, Sheng at the age of eight. Here is a concert record of mine. Hope you enjoy it!:)

I’m a “universal” ball fan and enjoy working out. If you cannot find me in office, catch me at the gym. 😃

Contact

Email: bowenj4[AT]illinois.edu