Haitao Mao

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 42

Top Topics

Link Prediction

Diffusion Models

Top Venues

Publications

Guangliang Liu, Haitao Mao, Jiliang Tang, Kristen Marie Johnson
Intrinsic Self-correction for Enhanced Morality: An Analysis of Internal Mechanisms and the Superficial Hypothesis. CoRR (2024)
Kaiwen Dong, Haitao Mao, Zhichun Guo, Nitesh V. Chawla
Universal Link Predictor By In-Context Learning on Graphs. CoRR (2024)
Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Qian Wang, Dawei Yin
Whole Page Unbiased Learning to Rank. WWW (2024)
Haitao Mao, Jianan Zhao, Xiaoxin He, Zhikai Chen, Qian Huang, Zhaocheng Zhu, Jian Tang, Michael M. Bronstein, Xavier Bresson, Bryan Hooi, Haiyang Zhang, Xianfeng Tang, Luo Chen, Jiliang Tang
The 1st International Workshop on Graph Foundation Models (GFM). WWW (Companion Volume) (2024)
Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang
A Data Generation Perspective to the Mechanism of In-Context Learning. CoRR (2024)
Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
Graph Foundation Models. CoRR (2024)
Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu
A Pure Transformer Pretraining Framework on Text-attributed Graphs. CoRR (2024)
Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. CoRR (2024)
Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
Label-free Node Classification on Graphs with Large Language Models (LLMs). ICLR (2024)
Guangliang Liu, Haitao Mao, Bochuan Cao, Zhiyu Xue, Kristen Marie Johnson, Jiliang Tang, Rongrong Wang
On the Intrinsic Self-Correction Capability of LLMs: Uncertainty and Latent Concept. CoRR (2024)
Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. CoRR (2024)
Wenqi Fan, Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li
Graph Machine Learning in the Era of Large Language Models (LLMs). CoRR (2024)
Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang
Source Free Graph Unsupervised Domain Adaptation. WSDM (2024)
Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Revisiting Link Prediction: a data perspective. ICLR (2024)
Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang
Neural Scaling Laws on Graphs. CoRR (2024)
Wenzhuo Tang, Haitao Mao, Danial Dervovic, Ivan Brugere, Saumitra Mishra, Yuying Xie, Jiliang Tang
Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models. CoRR (2024)
Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. KDD (2024)
Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang
LPFormer: An Adaptive Graph Transformer for Link Prediction. KDD (2024)
Junjie Xiang, Haitao Mao, Bin Yang
Impact assessment and mechanism of water conservancy policy on carbon emission performance under the background of artificial intelligence. Expert Syst. J. Knowl. Eng. 41 (5) (2024)
Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Qian Chen, Haitao Mao, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming. CoRR (2024)
Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang
Alternately Optimized Graph Neural Networks. ICML (2023)
Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs. CoRR (2023)
Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
Label-free Node Classification on Graphs with Large Language Models (LLMS). CoRR (2023)
Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? CoRR (2023)
Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
Exploring the Potential of Large Language Models (LLMs)in Learning on Graphs. SIGKDD Explor. 25 (2) (2023)
Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. CoRR (2023)
Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Revisiting Link Prediction: A Data Perspective. CoRR (2023)
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
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. NeurIPS (2023)
Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang
Adaptive Pairwise Encodings for Link Prediction. CoRR (2023)
Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. NeurIPS (2023)
Yanci Zhang, Mengjia Xia, Mingyang Li, Haitao Mao, Yutong Lu, Yupeng Lan, Jinlin Ye, Rui Dai
Form 10-K Itemization. CoRR (2023)
Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NeurIPS (2023)
Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. CoRR (2023)
Qiang Fu, Lun Du, Haitao Mao, Xu Chen, Wei Fang, Shi Han, Dongmei Zhang
Neuron with Steady Response Leads to Better Generalization. NeurIPS (2022)
Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Dawei Yin
Whole Page Unbiased Learning to Rank. CoRR (2022)
Lixin Zou, Haitao Mao, Xiaokai Chu, Jiliang Tang, Wenwen Ye, Shuaiqiang Wang, Dawei Yin
A Large Scale Search Dataset for Unbiased Learning to Rank. CoRR (2022)
Lixin Zou, Haitao Mao, Xiaokai Chu, Jiliang Tang, Wenwen Ye, Shuaiqiang Wang, Dawei Yin
A Large Scale Search Dataset for Unbiased Learning to Rank. NeurIPS (2022)
Haitao Mao, Xu Chen, Qiang Fu, Lun Du, Shi Han, Dongmei Zhang
Neuron Campaign for Initialization Guided by Information Bottleneck Theory. CoRR (2021)
Haitao Mao, Xu Chen, Qiang Fu, Lun Du, Shi Han, Dongmei Zhang
Neuron Campaign for Initialization Guided by Information Bottleneck Theory. CIKM (2021)
Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang
Source Free Unsupervised Graph Domain Adaptation. CoRR (2021)
Qiang Fu, Lun Du, Haitao Mao, Xu Chen, Wei Fang, Shi Han, Dongmei Zhang
Neuron with Steady Response Leads to Better Generalization. CoRR (2021)
Lei Zhang, Haitao Mao, Linlin Liu, Jian Du, Rafiqul Gani
A machine learning based computer-aided molecular design/screening methodology for fragrance molecules. Comput. Chem. Eng. 115 (2018)