Publications
Underline indicates student I mentored. * indicates equal contribution.
Network Science Insights towards Graph Foundation Models
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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 (335/9473)
Collaboration with SnapChat and Intel
[pdf] [Primary Blog] [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] -
Do Neural Scaling Laws Exist on Graph Self-Supervised Learning
Qian Ma, Haitao Mao, Jingzhe Liu, Zhehua Zhang, Chunlin Feng, Yu Song, Tianfan Fu, Yao Ma
Preprint [pdf][code] -
Neural Scaling Law on Graph
Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang
Collaboration with SnapChat
Preprint [pdf] [Blog]
LLM mechanisms
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Intrinsic Self-correction for Enhanced Morality: An Analysis of Internal Mechanisms and the Superficial Hypothesis
Guangliang Liu, Haitao Mao, Jiliang Tang, Kristen Johns.
Preprint [pdf] -
On the Intrinsic Self-Correction Capability of LLMs: Uncertainty and Latent Concept
Haitao Mao*, Guangliang Liu*, Bochuan Cao, Zhiyu Xue, Kristen Johnson, Jiliang Tang, Rongrong Wang
Preprint [pdf] -
A Data Generation Perspective to the Mechanism of In-Context Learning
Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang
Preprint [pdf]
Graph Foundation Models
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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][Code] -
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] -
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] -
Universal Link Predictor by In-Context Learning on Graphs
Kaiwen Dong, Haitao Mao, Zhichun Guo, Nitesh Chewla
Preprint [pdf] -
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] -
LPFormer: An Adaptive Graph Transformer for Link Prediction
Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang
KDD 2024
[pdf] [Code]
New Graph Applications
Graph Structure in the User Behavior
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Whole Page Unbiased Learning to Rank
Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Dawei Yin
WebConference 2024 Oral (198/2,008) [pdf]
Work During Internship in Baidu
Privacy-preserve Graph Structure Learning
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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 (3/615)
Work During Internship in Microsoft Research Asia
[pdf] [Blog] [Code]
Graph Structure in Leaning to Optimize
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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
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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]
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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
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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 Datasets & Benchmarks 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 ADS Track 2024
[pdf][Code]
Neuron Network Analysis
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Neuron Campaign for Initialization Guided by Information Bottleneck Theory
Haitao Mao*, Xu Chen*, Qiang Fu*, Lun Du*, Shi Han, Dongmei Zhang
CIKM2021 Best Short Paper (1/626)
Work During Internship in Microsoft Research Asia
[pdf] [Github] [Blog] [Chinese Blog] [Offical Poster] [Offical Slides] [Offical Video] [AI TIME Introduction] [AI TIME presentation Slides] [AI TIME Presentation Video] [AI TIME Report] -
Neuron with Steady Response Leads to Better Generalization
Haitao Mao*, Lun Du*, Qiang Fu*, Xu Chen*, Wei Fang, Shi Han, Dongmei Zhang
NeurIPS2022
Work During Internship in Microsoft Research Asia
[pdf] [Code] [Offical Video] [Official Slides] [Long Presentation Video] [Long Presentation Slides] [Poster] [Microsoft Research Asia News]
New LLM Applications in Data Mining
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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 Datasets & Benchmarks 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 Datasets and Benchmarks Track
Collaboration with Amazon
[pdf] [Homepage] [Instructions] [Code] [Poster]
