| Exploring the potential of large language models (llms) in learning on graphs Z Chen, H Mao, H Li, W Jin, H Wen, X Wei, S Wang, D Yin, W Fan, H Liu, ... ACM SIGKDD Explorations Newsletter 25 (2), 42-61, 2024 | 317 | 2024 |
| Label-free node classification on graphs with large language models (llms) Z Chen, H Mao, H Wen, H Han, W Jin, H Zhang, H Liu, J Tang International Conference on Learning Representations, 2024 | 71 | 2024 |
| Graph foundation models H Mao, Z Chen, W Tang, J Zhao, Y Ma, T Zhao, N Shah, M Galkin, J Tang Forty-first International Conference on Machine Learning, 2024 | 66* | 2024 |
| Demystifying structural disparity in graph neural networks: Can one size fit all? H Mao, Z Chen, W Jin, H Han, Y Ma, T Zhao, N Shah, J Tang Advances in neural information processing systems 36, 2023 | 64 | 2023 |
| Evaluating graph neural networks for link prediction: Current pitfalls and new benchmarking J Li, H Shomer, H Mao, S Zeng, Y Ma, N Shah, J Tang, D Yin Advances in Neural Information Processing Systems 36, 2023 | 63 | 2023 |
| Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation W Jin*, H Mao*, Z Li, H Jiang, C Luo, H Wen, H Han, H Lu, Z Wang, R Li, ... Advances in neural information processing systems 36, 2023 | 42 | 2023 |
| Source free graph unsupervised domain adaptation H Mao, L Du, Y Zheng, Q Fu, Z Li, X Chen, S Han, D Zhang Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | 39 | 2024 |
| Graph machine learning in the era of large language models (llms) W Fan, S Wang, J Huang, Z Chen, Y Song, W Tang, H Mao, H Liu, X Liu, ... arXiv preprint arXiv:2404.14928, 2024 | 28 | 2024 |
| A Large Scale Search Dataset for Unbiased Learning to Rank H Mao*, L Zou*, X Chu, J Tang, W Ye, S Wang, D Yin Advances in Neural Information Processing Systems 35, 2022 | 26 | 2022 |
| Revisiting link prediction: A data perspective H Mao, J Li, H Shomer, B Li, W Fan, Y Ma, T Zhao, N Shah, J Tang International Conference on Learning Representations, 2024 | 23 | 2024 |
| Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights Z Chen, H Mao, J Liu, Y Song, B Li, W Jin, B Fatemi, A Tsitsulin, B Perozzi, ... Advances in neural information processing systems 37, 2024 | 15 | 2024 |
| Neural scaling laws on graphs J Liu, H Mao, Z Chen, T Zhao, N Shah, J Tang Learning on Graphs Conference 2024, 2024 | 15 | 2024 |
| Alternately optimized graph neural networks H Han, X Liu, H Mao, MA Torkamani, F Shi, V Lee, J Tang International Conference on Machine Learning, 12411-12429, 2023 | 13 | 2023 |
| Neuron Campaign for Initialization Guided by Information Bottleneck Theory H Mao, X Chen, Q Fu, L Du, S Han, D Zhang Proceedings of the 30th ACM International Conference on Information …, 2021 | 12 | 2021 |
| LPFormer: an adaptive graph transformer for link prediction H Shomer, Y Ma, H Mao, J Li, B Wu, J Tang Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 9* | 2024 |
| A Survey to Recent Progress Towards Understanding In-Context Learning H Mao, G Liu, Y Ma, R Wang, J Tang NAACL 2025, 2025 | 8* | 2025 |
| Intrinsic self-correction for enhanced morality: An analysis of internal mechanisms and the superficial hypothesis G Liu, H Mao, J Tang, KM Johnson Conference on Empirical Methods in Natural Language Processing 2024, 2024 | 8 | 2024 |
| Company competition graph Y Zhang, Y Lu, H Mao, J Huang, C Zhang, X Li, R Dai arXiv preprint arXiv:2304.00323, 2023 | 6 | 2023 |
| Neuron with Steady Response Leads to Better Generalization H Mao*, Q Fu*, L Du*, X Chen, W Fang, S Han, D Zhang Advances in neural information processing systems 35, 2022 | 6 | 2022 |
| Cross-domain graph data scaling: A showcase with diffusion models W Tang, H Mao, D Dervovic, I Brugere, S Mishra, Y Xie, J Tang arXiv preprint arXiv:2406.01899, 2024 | 5 | 2024 |
