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Attention mechanisms have improved the performance of NLP tasks while allowing models to remain explainable.
Fine-tune BERT for extractive summarization
Yang Liu. 2019 · 1903
Earlier work this paper cites.
Sofia Serrano and Noah A Smith. 2019 · 1906
Earlier work this paper cites.
Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V Le. 2019 · 1906
Earlier work this paper cites.
Head-driven phrase structure grammar parsing on penn treebank
Junru Zhou and Hai Zhao. 2019 · 1907
Earlier work this paper cites.
Semi-supervised sequence modeling with cross-view training
Kevin Clark, Minh-Thang Luong, Christopher D Manning, and Quoc Le. 2018 · 1925
Earlier work this paper cites.
An efficient recognition and syntax-analysis algorithm for context-free languages
Tadao Kasami. 1966 · 1966
Earlier work this paper cites.
Recognition and parsing of context-free languages in time n3
Daniel H Younger. 1967 · 1967
Earlier work this paper cites.
Programming languages and their compilers: Preliminary notes
John Cocke. 1969 · 1969
Earlier work this paper cites.
Building a large annotated corpus of english: The penn treebank
Mitchell Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz. 1993 · 1993
Earlier work this paper cites.
Head-driven phrase structure grammar
Carl Pollard and Ivan A Sag. 1994 · 1994
Earlier work this paper cites.
Evalb bracket scoring program
Satoshi Sekine and Michael Collins. 1997 · 1997
Earlier work this paper cites.
Feature-rich part-of-speech tagging with a cyclic dependency network
Kristina Toutanova, Dan Klein, Christopher D Manning, and Yoram Singer. 2003 · 2003
Earlier work this paper cites.
The penn chinese treebank: Phrase structure annotation of a large corpus
Naiwen Xue, Fei Xia, Fu-Dong Chiou, and Marta Palmer. 2005 · 2005
Earlier work this paper cites.
A tale of two parsers: Investigating and combining graph-based and transition-based dependency parsing
Yue Zhang and Stephen Clark. 2008 · 2008
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Effective approaches to attention-based neural machine translation
Thang Luong, Hieu Pham, and Christopher D Manning. 2015 · 2015
Earlier work this paper cites.
Parsing as language modeling
Eugene Charniak et al. 2016 · 2016
Earlier work this paper cites.
Enhancing and combining sequential and tree lstm for natural language inference
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Cited alongside, same era.
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Do Kook Choe and Eugene Charniak. 2016 · 2016
Cited alongside, same era.
Deep biaffine attention for neural dependency parsing
Timothy Dozat and Christopher D Manning. 2016 · 2016
Cited alongside, same era.
Recurrent neural network grammars
Chris Dyer, Adhiguna Kuncoro, Miguel Ballesteros, and Noah A Smith. 2016 · 2016
Cited alongside, same era.
Distilling an ensemble of greedy dependency parsers into one MST parser
Adhiguna Kuncoro, Miguel Ballesteros, Lingpeng Kong, Chris Dyer, and Noah A. Smith. 2016 · 2016
Cited alongside, same era.
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Nikita Kitaev and Dan Klein. 2018 · 2018
Later among the works it cites.
Seq2seq dependency parsing
Zuchao Li, Jiaxun Cai, Shexia He, and Hai Zhao. 2018 · 2018
Later among the works it cites.
Stack-pointer networks for dependency parsing
Xuezhe Ma, Zecong Hu, Jingzhou Liu, Nanyun Peng, Graham Neubig, and Eduard Hovy. 2018 · 2018
Later among the works it cites.
Impact of corpora quality on neural machine translation
Matīss Rikters. 2018 · 2018
Later among the works it cites.
Training and adapting multilingual nmt for less-resourced and morphologically rich languages
Matīss Rikters, Mārcis Pinnis, and Rihards Krišlauks. 2018 · 2018
Later among the works it cites.
Straight to the tree: Constituency parsing with neural syntactic distance
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Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 · 2016
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Improving neural parsing by disentangling model combination and reranking effects
Daniel Fried, Mitchell Stern, and Dan Klein. 2017 · 2017
Cited alongside, same era.
What do recurrent neural network grammars learn about syntax?
Adhiguna Kuncoro, Miguel Ballesteros, Lingpeng Kong, Chris Dyer, Graham Neubig, and Noah A Smith. 2017 · 2017
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A structured self-attentive sentence embedding
Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, Mo Yu, Bing Xiang, Bowen Zhou, and Yoshua Bengio. 2017 · 2017
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Neural probabilistic model for non-projective MST parsing
Xuezhe Ma and Eduard Hovy. 2017 · 2017
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Attentive language models
Giancarlo Salton, Robert Ross, and John Kelleher. 2017 · 2017
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Mitchell Stern, Jacob Andreas, and Dan Klein. 2017 · 2017
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Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron Courville, and Yoshua Bengio. 2018 · 2018
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Linguistically-informed self-attention for semantic role labeling
Emma Strubell, Patrick Verga, Daniel Andor, David Weiss, and Andrew McCallum. 2018 · 2018
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An empirical study of building a strong baseline for constituency parsing
Jun Suzuki, Sho Takase, Hidetaka Kamigaito, Makoto Morishita, and Masaaki Nagata. 2018 · 2018
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Direct output connection for a high-rank language model
Sho Takase, Jun Suzuki, and Masaaki Nagata. 2018 · 2018
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Two local models for neural constituent parsing
Zhiyang Teng and Yue Zhang. 2018 · 2018
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Improved dependency parsing using implicit word connections learned from unlabeled data
Wenhui Wang, Baobao Chang, and Mairgup Mansur. 2018 · 2018
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Hierarchically-refined label attention network for sequence labeling
Leyang Cui and Yue Zhang. 2019 · 2019
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Left-to-right dependency parsing with pointer networks
Daniel Fernández-González and Carlos Gómez-Rodríguez. 2019 · 2019
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Attention is not explanation
Sarthak Jain and Byron C Wallace. 2019 · 2019
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Label-specific document representation for multi-label text classification
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