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This paper studies learning on text-attributed graphs (TAGs), where each node is associated with a text description.
Statistical analysis of non-lattice data
Julian Besag · 1975
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The” wake-sleep” algorithm for unsupervised neural networks
Geoffrey E Hinton, Peter Dayan, Brendan J Frey, and Radford M Neal · 1995
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A view of the em algorithm that justifies incremental, sparse, and other variants
Radford M. Neal and Geoffrey E. Hinton · 1998
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, and Christopher Potts · 2013
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Convolutional neural networks for sentence classification
Yoon Kim · 2014
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Learning semantic representations using convolutional neural networks for web search
Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng, and Grégoire Mesnil · 2014
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Improved semantic representations from tree-structured long short-term memory networks
Kai Sheng Tai, Richard Socher, and Christopher D Manning · 2015
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Inductive representation learning on large graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Graph attention networks
Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman · 2018
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Link prediction based on graph neural networks
Muhan Zhang and Yixin Chen · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Heterogeneous graph attention networks for semi-supervised short text classification
Linmei Hu, Tianchi Yang, Chuan Shi, Houye Ji, and Xiaoli Li · 2019
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Text level graph neural network for text classification
Lianzhe Huang, Dehong Ma, Sujian Li, Xiaodong Zhang, and Houfeng Wang · 2019
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Inductive relation prediction by subgraph reasoning
Komal K. Teru, Etienne G. Denis, and William L. Hamilton · 2020
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Every document owns its structure: Inductive text classification via graph neural networks
Yufeng Zhang, Xueli Yu, Zeyu Cui, Shu Wu, Zhongzhen Wen, and Liang Wang · 2020
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Leveraging bidding graphs for advertiser-aware relevance modeling in sponsored search
Shuxian Bi, Chaozhuo Li, Xiao Han, Zheng Liu, Xing Xie, Haizhen Huang, and Zengxuan Wen · 2021
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Deberta: decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen · 2021
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Scalable and adaptive graph neural networks with self-label-enhanced training
Chuxiong Sun and Guoshi Wu · 2021
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Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
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GMNN: graph markov neural networks
Meng Qu, Yoshua Bengio, and Jian Tang · 2019
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How powerful are graph neural networks?
Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le · 2019
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Don’t stop pretraining: Adapt language models to domains and tasks
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Open graph benchmark: Datasets for machine learning on graphs
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec · 2020
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Adsgnn: Behavior-graph augmented relevance modeling in sponsored search
Chaozhuo Li, Bochen Pang, Yuming Liu, Hao Sun, Zheng Liu, Xing Xie, Tianqi Yang, Yanling Cui, Liangjie Zhang, and Qi Zhang
Cited in the paper.
Graphformers: Gnn-nested transformers for representation learning on textual graph
Junhan Yang, Zheng Liu, Shitao Xiao, Chaozhuo Li, Defu Lian, Sanjay Agrawal, Amit Singh, Guangzhong Sun, and Xing Xie · 2021
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Textgnn: Improving text encoder via graph neural network in sponsored search
Jason Zhu, Yanling Cui, Yuming Liu, Hao Sun, Xue Li, Markus Pelger, Tianqi Yang, Liangjie Zhang, Ruofei Zhang, and Huasha Zhao · 2021
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Node feature extraction by self-supervised multi-scale neighborhood prediction
Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, and Inderjit S. Dhillon · 2022
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Improving relevance modeling via heterogeneous behavior graph learning in bing ads
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Linkbert: Pretraining language models with document links
Michihiro Yasunaga, Jure Leskovec, and Percy Liang · 2022
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Graph attention multi-layer perceptron
Wentao Zhang, Ziqi Yin, Zeang Sheng, Yang Li, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, and Bin Cui · 2022
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