Publications

Underline indicates student I mentored. * indicates equal contribution.

LLM Mechanism Analysis to Enhance Output Reliability

• Intrinsic Self-correction for Enhanced Morality: An Analysis of Internal Mechanisms and the Superficial Hypothesis
  Guangliang Liu, Haitao Mao, Jiliang Tang, Kristen Johns.
  EMNLP 2024
  [pdf][Short Summary]

• 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][Short Summary]

• A Data Generation Perspective to the Mechanism of In-Context Learning
  Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang
  Preprint [pdf][Short Summary]

Towards Versatile Graph Models

• 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][Short Summary][code]

• 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] [Blog] [Reading List 1] [Reading List 2]

• 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][Short Summary] [Slides]

• 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][Short Summary] [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
  LoG 2024
  [pdf][Short Summary]

• Universal Link Predictor by In-Context Learning on Graphs
  Kaiwen Dong, Haitao Mao, Zhichun Guo, Nitesh Chewla
  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
  LoG 2024
  [pdf][code]

• Neural Scaling Law on Graph
  Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang
  Collaboration with SnapChat
  LoG 2024
  [pdf][code] [Blog]

Identify Industry Challenges and Develop Resource Efficient Solutions

• 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] [Short Summary] [Homepage] [Instructions] [Code]

• 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][Short Summary]
  Work During Internship in Baidu
  

• 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][Short Summary] [Code1] [Code2] [Dataset Homepage2]

• 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][Short Summary] [Blog] [Code]

• 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][Short Summary] [Code] [Slides] [Poster]

• 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][Short Summary] [Code] [Blog] [Slides]

Graph & LLM

• 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
  NeurIPS 2024 Dataset & Benchmark Track
  [pdf][Short Summary][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][Short Summary] [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][Short Summary] [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]

Other Graph Mechine Learning Techniques

• 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]

• 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]

• 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]

• 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]