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One of the fundamental principles of contemporary linguistics states that language processing requires the ability to extract recursively nested tree structures.
Lstm networks can perform dynamic counting
Mirac Suzgun, Sebastian Gehrmann, Yonatan Belinkov, and Stuart M Shieber · 1906
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Memory-augmented recurrent neural networks can learn generalized dyck languages
Mirac Suzgun, Sebastian Gehrmann, Yonatan Belinkov, and Stuart M Shieber · 1911
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Syntactic Structures
Noam Chomsky · 1957
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The algebraic theory of context-free languages
Noam Chomsky and Marcel P Schützenberger · 1959
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The serial position effect of free recall
Bennet B Murdock Jr · 1962
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Distributed representations, simple recurrent networks, and grammatical structure
Jeffrey Elman · 1991
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The (non) necessity of recursion in natural language processing
Morten H Christiansen · 1992
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Learning to predict a context-free language: Analysis of dynamics in recurrent hidden units
Mikael Bodén, Janet Wiles, Bradley Tonkes, and Alan Blair · 1999
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Toward a connectionist model of recursion in human linguistic performance
Morten H Christiansen and Nick Chater · 1999
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Memory limitations and structural forgetting: The perception of complex ungrammatical sentences as grammatical
Edward Gibson and James Thomas · 1999
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Context-free and context-sensitive dynamics in recurrent neural networks
Mikael Bodén and Janet Wiles · 2000
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Finite models of infinite language: A connectionist approach to recursion
Morten H Christiansen and Nick Chater · 2001
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LSTM recurrent networks learn simple context-free and context-sensitive languages
Felix Gers and Jürgen Schmidhuber · 2001
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Simple recurrent networks learn context-free and context-sensitive languages by counting
Paul Rodriguez · 2001
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The faculty of language: What is it, who has it, and how did it evolve?
Marc Hauser, Noam Chomsky, and Tecumseh Fitch · 2002
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Visualisation and ’diagnostic classifiers’ reveal how recurrent and recursive neural networks process hierarchical structure
Dieuwke Hupkes, Sara Veldhoen, and Willem Zuidema · 2018
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Jaap Jumelet and Dieuwke Hupkes · 2018
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Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks
Brenden Lake and Marco Baroni · 2018
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Targeted syntactic evaluation of language models
Rebecca Marvin and Tal Linzen · 2018
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Ordered neurons: Integrating tree structures into recurrent neural networks
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The neural representation of sequences: From transition probabilities to algebraic patterns and linguistic trees
Stanislas Dehaene, Florent Meyniel, Catherine Wacongne, Liping Wang, and Christophe Pallier · 2015
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Inferring algorithmic patterns with stack-augmented recurrent nets
Armand Joulin and Tomas Mikolov · 2015
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Assessing the ability of LSTMs to learn syntax-sensitive dependencies
Tal Linzen, Emmanuel Dupoux, and Yoav Goldberg · 2016
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Using deep neural networks to learn syntactic agreement
Jean-Philippe Bernardy and Shalom Lappin · 2017
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Can recurrent neural networks learn nested recursion?
Jean-Philippe Bernardy · 2018
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Rnns as psycholinguistic subjects: Syntactic state and grammatical dependency
Richard Futrell, Ethan Wilcox, Takashi Morita, and Roger Levy · 2018
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Colorless green recurrent networks dream hierarchically
Kristina Gulordava, Piotr Bojanowski, Edouard Grave, Tal Linzen, and Marco Baroni · 2018
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Yikang Shen, Shawn Tan, Alessandro Sordoni, and Aaron Courville · 2018
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On evaluating the generalization of lstm models in formal languages
Mirac Suzgun, Yonatan Belinkov, and Stuart M Shieber · 2018
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On the practical computational power of finite precision rnns for language recognition
Gail Weiss, Yoav Goldberg, and Eran Yahav · 2018
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Assessing bert’s syntactic abilities
Yoav Goldberg · 2019
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The compositionality of neural networks: integrating symbolism and connectionism
Dieuwke Hupkes, Verna Dankers, Mathijs Mul, and Elia Bruni · 2019
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The emergence of number and syntax units in lstm language models
Yair Lakretz, German Kruszewski, Theo Desbordes, Dieuwke Hupkes, Stanislas Dehaene, and Marco Baroni · 2019
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What syntactic structures block dependencies in rnn language models?
Ethan Wilcox, Roger Levy, and Richard Futrell · 2019
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