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Dialogue relation extraction (RE) is to predict the relation type of two entities mentioned in a dialogue.
“Symmetric regularization based bert for pair-wise semantic reasoning,”
Weidi Xu, Xingyi Cheng, Kunlong Chen, and Taifeng Wang, · 1904
Earlier work this paper cites.
“Soft-DTW: a differentiable loss function for time-series,”
Marco Cuturi and Mathieu Blondel, · 2017
Earlier work this paper cites.
“Position-aware attention and supervised data improve slot filling,”
Yuhao Zhang, Victor Zhong, Danqi Chen, Gabor Angeli, and Christopher D. Manning, · 2017
Earlier work this paper cites.
“BERT: Pre-training of deep bidirectional transformers for language understanding,”
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova, · 2019
Earlier work this paper cites.
“How does bert answer questions? a layer-wise analysis of transformer representations,”
Betty van Aken, Benjamin Winter, Alexander Löser, and Felix A. Gers, · 2019
Earlier work this paper cites.
“Fine-tune bert for extractive summarization,”
Yang Liu, · 2019
Earlier work this paper cites.
“Group, extract and aggregate: Summarizing a large amount of finance news for forex movement prediction,”
Deli Chen, Shuming Ma, Keiko Harimoto, Ruihan Bao, Qi Su, and Xu Sun, · 2019
Cited alongside, same era.
“Shallow-deep networks: Understanding and mitigating network overthinking,”
Yigitcan Kaya, Sanghyun Hong, and Tudor Dumitras, · 2019
Cited alongside, same era.
“Attention guided graph convolutional networks for relation extraction,”
Zhijiang Guo, Yan Zhang, and Wei Lu, · 2019
Cited alongside, same era.
“Knowledge enhanced contextual word representations,”
Matthew E. Peters, Mark Neumann, Robert Logan, Roy Schwartz, Vidur Joshi, Sameer Singh, and Noah A. Smith, · 2019
Cited alongside, same era.
“Dialogue-based relation extraction,”
Dian Yu, Kai Sun, Claire Cardie, and Dong Yu, · 2020
Cited alongside, same era.
“Gdpnet: Refining latent multi-view graph for relation extraction,”
“Dialogue relation extraction with document-level heterogeneous graph attention networks,”
Hui Chen, Pengfei Hong, Wei Han, Navonil Majumder, and Soujanya Poria, · 2020
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“Vl-bert: Pre-training of generic visual-linguistic representations,”
Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, and Jifeng Dai, · 2020
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“Reasoning with latent structure refinement for document-level relation extraction,”
Guoshun Nan, Zhijiang Guo, Ivan Sekulic, and Wei Lu, · 2020
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“Relation extraction with convolutional network over learnable syntax-transport graph,”
Kai Sun, Richong Zhang, Yongyi Mao, Samuel Mensah, and Xudong Liu, · 2020
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“SpanBERT: Improving pre-training by representing and predicting spans,”
Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, and Omer Levy, · 2020
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Fuzhao Xue, Aixin Sun, Hao Zhang, and Eng Siong Chng, · 2020
Cited alongside, same era.