Underline indicates student mentored. *represents equal contribution.

LLM mechanism (and toy NN)

Graph Mechanism towards Graph Foundation Models

  • Position: Graph Foundation Models Are Already Here
    Haitao Mao*, Zhikai Chen*, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
    ICML 2024 spotlight
    collaboration with SnapChat and Intel
    [pdf] [blog] [reading List 1] [reading List 2]

  • Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
    Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
    NeurIPS 2023
    collaboration with SnapChat
    [pdf] [code] [slides] [poster] [video]

  • Revisiting Link Prediction: A data perspective
    Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
    ICLR 2024
    collaboration with SnapChat
    [pdf] [slides] [video]

  • Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models
    Wenzhuo Tang, Haitao Mao, Danial Dervovic, Ivan Brugere, Saumitra Mishra, Yuying Xie, Jiliang Tang
    collaboration with JP Morgan
    preprint [pdf]

  • Text-space graph foundation models: a comprehensive benchmark and new insights
    Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
    collaboration with Google
    preprint [pdf]

  • Do Neural Scaling Laws exist on Graph Self-Supervised Learning
    Qian Ma, Haitao Mao, Zhehua Zhang, Chunlin Feng, Jingzhe Liu, Yu Song, Yao Ma
    preprint [pdf]

  • Universal Link Predictor by In-Context Learning on Graphs
    Kaiwen Dong, Haitao Mao, Zhichun Guo, Nitesh Chewla
    preprint [pdf]

  • Neural Scaling Law on Graph
    Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang
    collaboration with SnapChat
    preprint [pdf] [blog]

  • A Pure Transformer Pretraining Framework on Text-attributed Graphs
    Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu
    preprint [pdf]

New Graph applications

Graph Structure in the User Behavior

  • Whole Page Unbiased Learning to Rank
    Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Dawei Yin
    WebConference 2024 Oral [pdf]
    Work during internship in Baidu

Privacy-preserve Graph structure learning

  • Source Free Graph Unsupervised Domain Adaptation
    Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang
    WSDM 2024 Best Paper Honor Mention
    Work during internship in Microsoft Research Asia
    [pdf] [blog] [code]

Graph Structure in Leaning to Optimize

  • PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
    Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Qian Chen, Haitao Mao, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun
    ICML 2024
    [pdf]

Graph Structure in the Finance Domain

  • Company Competition Graph
    Yanci Zhang, Yutong Lu, Haitao Mao, Jiawei Huang, Cien Zhang, Xinyi Li, Rui Dai
    MAF 2024
    collaboration with Wharton Data Center
    [pdf]

  • Form 10-K Itemization
    Yanci Zhang, Mengjia Xia, Mingyang Li, Haitao Mao, Yutong Lu, Yupeng Lan, Jinlin Ye, Rui Dai
    collaboration with Wharton Data Center
    preprint [pdf]

Benchmarking

  • Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
    Juanhui Li*, Harry Shomer*, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
    NeurIPS 2023 Dataset Track
    collaboration with SnapChat
    [pdf] [code] [poster]

  • Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark
    Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma
    KDD 2024
    [pdf][code]

New LLM applications in Data Mining

  • A Large Scale Search Dataset for Unbiased Learning to Rank
    Haitao Mao*, Lixin Zou*, Xiaokai Chu, Jiliang Tang, Shuaiqiang Wang, Wenwen ye, Dawei yin.
    NeurIPS 2022 Dataset Track
    Work during internship in Baidu
    [pdf] [Code1] [Code2] [Dataset Homepage1] [Dataset Homepage2] [Long presentation video] [Long presentation slides] [Poster]

  • Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
    Wei Jin*, Haitao Mao*, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, and Xianfeng Tang
    NeurIPS 2022 Dataset Track
    collaboration with Amazon
    [pdf] [homepage] [instructions] [code] [poster]

  • Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
    Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
    SIGKDD Explorations 2023
    collaboration with Baidu
    [pdf] [code] [slides]

  • Label-free Node Classification on Graphs with Large Language Models (LLMS)
    Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
    ICLR 2024
    collaboration with Amazon
    [pdf] [code] [slides]

  • Graph Machine Learning in the Era of Large Language Models (LLMs)
    Wenqi Fan, Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang,
    Haitao Mao, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li
    [pdf]

Others

  • AI4Science101: Graph Machine Learning
    Haitao Mao, Yuanqi Du, Yanbang Wang
    [blog page]

  • LPFormer: An Adaptive Graph Transformer for Link Prediction
    Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang
    KDD 2024
    [pdf] [code]

  • Alternately Optimized Graph Neural Network
    Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang
    collaboration with TigerGraph
    ICML 2023
    [pdf] [code]