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Relation Extraction (RE) is to predict the relation type of two entities that are mentioned in a piece of text, e.g., a sentence or a dialogue.
Long short-term memory
Hochreiter, S.; and Schmidhuber, J. 1997 · 1997
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Face recognition: a convolutional neural-network approach
Lawrence, S.; Giles, C. L.; Ah Chung Tsoi; and Back, A. D. 1997 · 1997
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Diffusion-Convolutional Neural Networks
Atwood, J.; and Towsley, D. 2016 · 2001
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Efficient long-distance relation extraction with DG-SpanBERT
Chen, J.; Hoehndorf, R.; Elhoseiny, M.; and Zhang, X. 2020 · 2004
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Framewise Phoneme Classification with Bidirectional LSTM and Other Neural Network Architectures
Graves, A.; and Schmidhuber, J. 2005 · 2005
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Modeling Joint Entity and Relation Extraction with Table Representation
Miwa, M.; and Sasaki, Y. 2014 · 2014
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Improved Relation Extraction with Feature-Rich Compositional Embedding Models
Gormley, M. R.; Yu, M.; and Dredze, M. 2015 · 2015
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Learning to Represent Knowledge Graphs with Gaussian Embedding
He, S.; Liu, K.; Ji, G.; and Zhao, J. 2015 · 2015
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Adam: A Method for Stochastic Optimization
Kingma, D. P.; and Ba, J. 2015 · 2015
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Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification
Zhou, P.; Shi, W.; Tian, J.; Qi, Z.; Li, B.; Hao, H.; and Xu, B. 2016 · 2016
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Soft-DTW: a Differentiable Loss Function for Time-Series
Cuturi, M.; and Blondel, M. 2017 · 2017
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Neural Machine Translation with Source-Side Latent Graph Parsing
Hashimoto, K.; and Tsuruoka, Y. 2017 · 2017
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Dynamic edge-conditioned filters in convolutional neural networks on graphs
Simonovsky, M.; and Komodakis, N. 2017 · 2017
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Position-aware Attention and Supervised Data Improve Slot Filling
Zhang, Y.; Zhong, V.; Chen, D.; Angeli, G.; and Manning, C. D. 2017 · 2017
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A Walk-based Model on Entity Graphs for Relation Extraction
Christopoulou, F.; Miwa, M.; and Ananiadou, S. 2018 · 2018
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Hierarchical Graph Representation Learning with Differentiable Pooling
Ying, Z.; You, J.; Morris, C.; Ren, X.; Hamilton, W.; and Leskovec, J. 2018 · 2018
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Graph Convolution over Pruned Dependency Trees Improves Relation Extraction
Zhang, Y.; Qi, P.; and Manning, C. D. 2018 · 2018
Knowledge Enhanced Contextual Word Representations
Peters, M. E.; Neumann, M.; Logan, R.; Schwartz, R.; Joshi, V.; Singh, S.; and Smith, N. A. 2019 · 2019
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Enriching Pre-Trained Language Model with Entity Information for Relation Classification
Wu, S.; and He, Y. 2019 · 2019
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StructPool: Structured graph pooling via conditional random fields
Yuan, H.; and Ji, S. 2019 · 2019
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TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction Task
Alt, C.; Gabryszak, A.; and Hennig, L. 2020 · 2020
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Learning Latent Forests for Medical Relation Extraction
Guo, Z.; Nan, G.; LU, W.; and Cohen, S. B. 2020 · 2020
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SpanBERT: Improving Pre-training by Representing and Predicting Spans
Joshi, M.; Chen, D.; Liu, Y.; Weld, D. S.; Zettlemoyer, L.; and Levy, O. 2020 · 2020
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Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs
Christopoulou, F.; Miwa, M.; and Ananiadou, S. 2019 · 2019
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
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Attention Guided Graph Convolutional Networks for Relation Extraction
Guo, Z.; Zhang, Y.; and Lu, W. 2019 · 2019
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Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning
Guo, Z.; Zhang, Y.; Teng, Z.; and Lu, W. 2019 · 2019
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Self-Attention Graph Pooling
Lee, J.; Lee, I.; and Kang, J. 2019 · 2019
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Reasoning with Latent Structure Refinement for Document-Level Relation Extraction
Nan, G.; Guo, Z.; Sekulic, I.; and Lu, W. 2020 · 2020
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Relation Extraction with Convolutional Network over Learnable Syntax-Transport Graph
Sun, K.; Zhang, R.; Mao, Y.; Mensah, S.; and Liu, X. 2020 · 2020
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Dialogue-Based Relation Extraction
Yu, D.; Sun, K.; Cardie, C.; and Yu, D. 2020 · 2020
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Graph U-Nets
Gao, H.; and Ji, S. 2019 · 2092
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