I am a first-year Ph.D. student majoring in Data Science at The University of Hong Kong (HKU), supervised by Prof. Chao Huang and Kao, Benjamin C.M.

My research interest includes Graph Neural Networks, Large Language Models and deep learning applications. I have published some papers at the top international AI conferences such as KDD, SIGIR, CIKM, WWW.

🔥 News

  • 🎯 2024.03:  🎉🎉Our HiGPT is accepted by KDD’24 in the Research Track (~20% acceptance rate), UrbanGPT is accepted by KDD’24 in the Applied Data Science Track (~20% acceptance rate) and LLM4Graph is accepted by KDD’24 in the Lecture-Style Track Tutorial. Check out more about HiGPT: 🏠https://higpt-hku.github.io/, UrbanGPT: 🏠https://urban-gpt.github.io/ and LLM4Graph: 🏠https://github.com/HKUDS/Awesome-LLM4Graph-Papers. Thanks to Zhonghang, Xubin and other co-authors as well as my supervisor!

  • 🎯 2024.03:  🎉🎉Our GraphGPT is accepted by SIGIR’24 in the Full paper track (20.1% acceptance rate). Check out more about GraphGPT: 🏠https://graphgpt.github.io/. Thanks to all my co-authors and my supervisor!
  • 🎯 2024.03:  🎉🎉I gave a presentation titled “Graph Language Models” on 24rd March 2024 in Talk on MLLM to introduce our GraphGPT, HiGPT and UrbanGPT. Please check out this [video] !
  • 🎯 2024.02:  🎉🎉 We release our Heterogeneous Graph Language Model - HiGPT with pre-print paper, source code, model. Goodbye, homogeneous graphs! Hi, heterogeneous graph!
  • 🎯 2023.10:  🎉🎉 We release our Graph Large Language Models - GraphGPT with pre-print paper, source code, model and data. Let’s step to Graph Learning in the era of LLM!
  • 🎯 2024.03:  🎉🎉 We release our Spatio-Temporal Large Language Models - UrbanGPT with pre-print paper, source code, model and data. Keep going towards smart city in the era of LLMs!
  • 2024.02:  🎉🎉 Our paper PromptMM is accepted by WWW’24! Thanks to Wei Wei and other co-authors!
  • 2023.10:  🎉🎉 Our paper LLMRec is accepted by WSDM’24! Thanks to Wei Wei and other co-authors!
  • 2023.08:  🎉🎉 Two full papers about spatio-temporal data mining are accepted by CIKM’23. Thanks to all my co-authors and my supervisor!
More News
  • 2023.06:  ðŸŽ‰ðŸŽ‰ I graduated from SWJTU. Nice memories with all my friends, teachers and family!
  • 2022.11:  ðŸŽ‰ðŸŽ‰ I am honored with Cao Jianyou Student Award 2022 (Selected from eight universities, including Southwest Jiaotong University, Tongji University, Central South University, etc. ).
  • 2022.11:  ðŸŽ‰ðŸŽ‰ I am nominated for National Scholarship for Encouragement and Provincial Outstanding Graduates.

📝 Publications

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

Survey

A Survey of Large Language Models for Graphs, [code]

Xubin Ren, Jiabin Tang, Dawei Yin, Nitesh Chawla, Chao Huang$^{\dagger}$

  • in Proc. of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.

Tutorials

&Large Language Models for Graphs: Progresses and Directions, [code], [project]

Chao Huang$^{\dagger}$, Xubin Ren, Jiabin Tang, Dawei Yin, Nitesh Chawla

  • in Proc. of The Web Conference (WWW), 2024 and ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.

Conference and Journal Publications

🎯GraphGPT: Graph Instruction Tuning for Large Language Models, [code], [project], [Bilibili], [Youtube]  

Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Lixin Su, Suqi Cheng, Dawei Yin, Chao Huang$^{\dagger}$

  • in Proc. of Special Interest Group on Information Retrieval (SIGIR), 2024.

🎯HiGPT: Heterogeneous Graph Language Model, [code], [project]  

Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Long Xia, Dawei Yin, Chao Huang$^{\dagger}$

  • in Proc. of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.

🎯UrbanGPT: Spatio-Temporal Large Language Models, [code], [project], [video]

Zhonghang Li, Lianghao Xia, Jiabin Tang, Yong Xu, Lei Shi, Long Xia, Dawei Yin, Chao Huang$^{\dagger}$

  • in Proc. of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.

PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning, [code]

Wei Wei, Jiabin Tang, Yangqin Jiang, Lianghao Xia, Chao Huang$^{\dagger}$

  • in Proc. of The Web Conference (WWW), 2024.

LLMRec: Large Language Models with Graph Augmentation for Recommendation, [code], [project]

Wei Wei, Xubin Ren, Jiabin Tang, Qinyong Wang, Lixin Su, Suqi Cheng, junfeng wang, Dawei Yin, Chao Huang$^{\dagger}$

  • in Proc. of The ACM International Conference on Web Search and Data Mining (WSDM), 2024. (Oral Presentation)

Spatio-Temporal Meta Contrastive Learning, [code]  

Jiabin Tang, Lianghao Xia, Jie Hu, Chao Huang$^{\dagger}$

  • in Proc. of The ACM International Conference on Information and Knowledge Management (CIKM), 2023.

Explainable Spatio-Temporal Graph Neural Networks, [code]  

Jiabin Tang, Lianghao Xia, Chao Huang$^{\dagger}$

  • in Proc. of The ACM International Conference on Information and Knowledge Management (CIKM), 2023.

Spatio-Temporal Latent Graph Structure Learning for Traffic Forecasting

Jiabin Tang, Tang Qian, Shijing Liu, Shengdong Du$^{\dagger}$, Jie Hu, Tianrui Li

  • in Proc. of The International Joint Conference on Neural Networks (IJCNN), 2022. (Oral Presentation)

🎖 Honors and Awards

  • Scholarship(Selected)
    • National Scholarship (Two Times): 2020 and 2021
    • Cao Jianyou Student Award: 2022
    • National Scholarship for Encouragement: 2022
    • Provincial Outstanding Graduates: 2023

📖 Educations

  • 2023.09 - 2027.06 (expected), Ph.D. in Data Science, The University of Hong Kong (HKU)

  • 2019.09 - 2023.06, B. Eng in Software Engineering, Southwest Jiaotong University (SWJTU)

💬 Invited Talks

  • 2024.03: Giving a presentation titled “Graph Language Models” on 24rd March 2024 in Talk on MLLM to introduce our GraphGPT, HiGPT and UrbanGPT. video
  • 2023.12, Sharing our ‘GraphGPT: Graph Instruction Tuning for Large Language Models’ online in the Bilibili Channel AITIME论道, video
  • 2023.10, Oral presentation at CIKM 2023 about our paper: ‘Spatio-Temporal Meta Contrastive Learning’ and ‘Explainable Spatio-Temporal Graph Neural Networks’.
  • 2022.08, Oral presentation at IJCNN 2022 about our paper: ‘Spatio-Temporal Latent Graph Structure Learning for Traffic Forecasting’.

🧑‍💻 Service

  • As an organizer of Talk on MLLM platform.
  • Conference Reviewers:
    • KDD, CIKM: 2024
  • Journal Reviewers:
    • TNNLS

💻 Internships

  • Research Intern
    • Company/Institution: Search Science Team, Baidu Inc.
    • Advisor: Dr. Lei Shi & Dr. Lixin Su
    • Employment period: From 06/2023 to the present
  • Research Intern
    • Company/Institution: Data Intelligence Lab, The University of Hong Kong
    • Advisor: Prof. Chao Huang
    • Employment period: From 01/2022 to the present
  • Research Intern
    • Company/Institution: CCIT Laboratory, Southwest Jiaotong University
    • Advisor: Prof. Tianrui Li & Prof. Shengdong Du
    • Employment period: From 09/2021 to 04/2022