Mao, Haitao

17 publications

LoG 2025 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

NeurIPS 2025 Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models Wenzhuo Tang, Haitao Mao, Danial Dervovic, Ivan Brugere, Saumitra Mishra, Yuying Xie, Jiliang Tang

LoG 2025 Do Neural Scaling Laws Exist on Graph Self-Supervised Learning? Qian Ma, Haitao Mao, Jingzhe Liu, Zhehua Zhang, Chunlin Feng, Yu Song, Yihan Shao, Yao Ma

LoG 2025 Towards Neural Scaling Laws on Graphs Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang

TMLR 2025 Universal Link Predictor by In-Context Learning on Graphs Kaiwen Dong, Haitao Mao, Zhichun Guo, Nitesh V Chawla

ICLR 2024 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

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

ICML 2024 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

ICLR 2024 Revisiting Link Prediction: A Data Perspective Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang

NeurIPS 2024 Text-Space Graph Foundation Models: Comprehensive Benchmarks 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

ICML 2023 Alternately Optimized Graph Neural Networks Haoyu Han, Xiaorui Liu, Haitao Mao, Mohamadali Torkamani, Feng Shi, Victor Lee, Jiliang Tang

NeurIPS 2023 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, Xianfeng Tang

NeurIPS 2023 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 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

NeurIPSW 2023 Exploring the Potential of Large Language Models (LLMs) in Learning on Graph Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang

NeurIPS 2022 A Large Scale Search Dataset for Unbiased Learning to Rank Lixin Zou, Haitao Mao, Xiaokai Chu, Jiliang Tang, Wenwen Ye, Shuaiqiang Wang, Dawei Yin

NeurIPS 2022 Neuron with Steady Response Leads to Better Generalization Qiang Fu, Lun Du, Haitao Mao, Xu Chen, Wei Fang, Shi Han, Dongmei Zhang