Haitao Mao

According to our database, Haitao Mao authored at least 35 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Impact assessment and mechanism of water conservancy policy on carbon emission performance under the background of artificial intelligence.

Junjie Xiang, Haitao Mao, Bin Yang

Expert Syst. J. Knowl. Eng., May, 2024

Research on Network Teaching Collaboration Platform Using Flipped Classroom Teaching Mode.

Jing Zhao, Haitao Mao, Panpan Mao, Junyong Hao, Meige Mao

J. Inf. Knowl. Manag., April, 2024

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

CoRR, 2024

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

CoRR, 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

CoRR, 2024

On the Intrinsic Self-Correction Capability of LLMs: Uncertainty and Latent Concept.

Guangliang Liu, Haitao Mao, Bochuan Cao, Zhiyu Xue, Kristen Marie Johnson, Jiliang Tang, Rongrong Wang

CoRR, 2024

Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models.

Wenzhuo Tang, Haitao Mao, Danial Dervovic, Ivan Brugere, Saumitra Mishra, Yuying Xie, Jiliang Tang

CoRR, 2024

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

CoRR, 2024

Universal Link Predictor By In-Context Learning on Graphs.

Kaiwen Dong, Haitao Mao, Zhichun Guo, Nitesh V. Chawla

CoRR, 2024

Graph Foundation Models.

Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang

CoRR, 2024

A Data Generation Perspective to the Mechanism of In-Context Learning.

Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang

CoRR, 2024

Neural Scaling Laws on Graphs.

Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang

CoRR, 2024

Whole Page Unbiased Learning to Rank.

Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Qian Wang, Dawei Yin

Proceedings of the ACM on Web Conference 2024, 2024

The 1st International Workshop on Graph Foundation Models (GFM).

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

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Source Free Graph Unsupervised Domain Adaptation.

Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

LPFormer: An Adaptive Graph Transformer for Link Prediction.

Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

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

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 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

Proceedings of the Forty-first International Conference on Machine Learning, 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

Proceedings of the Forty-first International Conference on Machine Learning, 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

Proceedings of the Twelfth International Conference on Learning Representations, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Intrinsic Self-correction for Enhanced Morality: An Analysis of Internal Mechanisms and the Superficial Hypothesis.

Guangliang Liu, Haitao Mao, Jiliang Tang, Kristen Marie Johnson

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

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 Explor., December, 2023

Adaptive Pairwise Encodings for Link Prediction.

Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang

CoRR, 2023

Form 10-K Itemization.

Yanci Zhang, Mengjia Xia, Mingyang Li, Haitao Mao, Yutong Lu, Yupeng Lan, Jinlin Ye, Rui Dai

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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 Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Alternately Optimized Graph Neural Networks.

Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang

Proceedings of the International Conference on Machine Learning, 2023

2022

Whole Page Unbiased Learning to Rank.

Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Dawei Yin

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Neuron with Steady Response Leads to Better Generalization.

Qiang Fu, Lun Du, Haitao Mao, Xu Chen, Wei Fang, Shi Han, Dongmei Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Source Free Unsupervised Graph Domain Adaptation.

Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang

CoRR, 2021

Neuron Campaign for Initialization Guided by Information Bottleneck Theory.

Haitao Mao, Xu Chen, Qiang Fu, Lun Du, Shi Han, Dongmei Zhang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2018

A machine learning based computer-aided molecular design/screening methodology for fragrance molecules.

Lei Zhang, Haitao Mao, Linlin Liu, Jian Du, Rafiqul Gani

Comput. Chem. Eng., 2018