Iterative deep graph learning for graph neural networks: Better and robust node embeddings Y Chen, L Wu, M Zaki Advances in neural information processing systems 33, 19314-19326, 2020 | 389 | 2020 |
A joint neural model for information extraction with global features Y Lin, H Ji, F Huang, L Wu Proceedings of the 58th annual meeting of the association for computational …, 2020 | 362 | 2020 |
Graph neural networks: foundation, frontiers and applications L Wu, P Cui, J Pei, L Zhao, X Guo Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 313 | 2022 |
Improved code summarization via a graph neural network A LeClair, S Haque, L Wu, C McMillan Proceedings of the 28th international conference on program comprehension …, 2020 | 305 | 2020 |
Graph neural networks for natural language processing: A survey L Wu, Y Chen, K Shen, X Guo, H Gao, S Li, J Pei, B Long Foundations and Trends® in Machine Learning 16 (2), 119-328, 2023 | 259 | 2023 |
Graph2seq: Graph to sequence learning with attention-based neural networks K Xu, L Wu, Z Wang, Y Feng, M Witbrock, V Sheinin arXiv preprint arXiv:1804.00823, 2018 | 210 | 2018 |
Reinforcement learning based graph-to-sequence model for natural question generation Y Chen, L Wu, MJ Zaki arXiv preprint arXiv:1908.04942, 2019 | 186 | 2019 |
Knowledge graph-augmented abstractive summarization with semantic-driven cloze reward L Huang, L Wu, L Wang arXiv preprint arXiv:2005.01159, 2020 | 176 | 2020 |
Bidirectional attentive memory networks for question answering over knowledge bases Y Chen, L Wu, MJ Zaki arXiv preprint arXiv:1903.02188, 2019 | 173 | 2019 |
Quantized densely connected u-nets for efficient landmark localization Z Tang, X Peng, S Geng, L Wu, S Zhang, D Metaxas Proceedings of the European conference on computer vision (ECCV), 339-354, 2018 | 157 | 2018 |
Word mover's embedding: From word2vec to document embedding L Wu, IEH Yen, K Xu, F Xu, A Balakrishnan, PY Chen, P Ravikumar, ... arXiv preprint arXiv:1811.01713, 2018 | 134 | 2018 |
Improved automatic summarization of subroutines via attention to file context S Haque, A LeClair, L Wu, C McMillan Proceedings of the 17th International Conference on Mining Software …, 2020 | 114 | 2020 |
Heterogeneous global graph neural networks for personalized session-based recommendation Y Pang, L Wu, Q Shen, Y Zhang, Z Wei, F Xu, E Chang, B Long, J Pei Proceedings of the fifteenth ACM international conference on web search and …, 2022 | 110 | 2022 |
Reinforcement learning based text style transfer without parallel training corpus H Gong, S Bhat, L Wu, JJ Xiong, W Hwu arXiv preprint arXiv:1903.10671, 2019 | 106 | 2019 |
Robustness of graph neural networks at scale S Geisler, T Schmidt, H Şirin, D Zügner, A Bojchevski, S Günnemann Advances in Neural Information Processing Systems 34, 7637-7649, 2021 | 105 | 2021 |
Exploiting rich syntactic information for semantic parsing with graph-to-sequence model K Xu, L Wu, Z Wang, M Yu, L Chen, V Sheinin arXiv preprint arXiv:1808.07624, 2018 | 102 | 2018 |
Discrete adversarial attacks and submodular optimization with applications to text classification Q Lei, L Wu, PY Chen, A Dimakis, IS Dhillon, MJ Witbrock Proceedings of Machine Learning and Systems 1, 146-165, 2019 | 99 | 2019 |
Similarity preserving representation learning for time series clustering Q Lei, J Yi, R Vaculin, L Wu, IS Dhillon arXiv preprint arXiv:1702.03584, 2017 | 95 | 2017 |
Sql-to-text generation with graph-to-sequence model K Xu, L Wu, Z Wang, Y Feng, V Sheinin arXiv preprint arXiv:1809.05255, 2018 | 91 | 2018 |
Graphflow: Exploiting conversation flow with graph neural networks for conversational machine comprehension Y Chen, L Wu, MJ Zaki arXiv preprint arXiv:1908.00059, 2019 | 87 | 2019 |