---
title: "Who cites What Do Recurrent Neural — 73 citing papers"
description: "73 papers of the Elamur Research library cite «What Do Recurrent Neural Network Grammars Learn About Syntax?», found in their…"
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# Who cites «What Do Recurrent Neural Network Grammars Learn About Syntax?»

73 papers of our library cite it (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · [← back to «What Do Recurrent Neural Network Grammars Learn About Syntax?»](https://md.research.elamur.ai/free/en/papers/kuncoro-2016-recurrent-neural-network-grammars-learn/)

1. **[How Can We Know What Language Models Know?](https://md.research.elamur.ai/free/en/papers/jiang-2020-how-can-we-know-what/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhengbao Jiang, Frank F. Xu, Jun Araki, et al.*2020 · 1,521 citations*
2. [**Deep Biaffine Attention for Neural Dependency Parsing**Timothy Dozat, Christopher D. Manning*2016 · 1,326 citations*](https://md.research.elamur.ai/free/en/papers/dozat-2016-deep-biaffine-attention-neural-dependency/)
3. **[Linguistic Knowledge and Transferability of Contextual Representations](https://md.research.elamur.ai/free/en/papers/liu-2019-linguistic-knowledge-transferability-contextual-representations/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nelson F. Liu, Matt Gardner, Yonatan Belinkov, et al.*2019 · 1,021 citations*
4. **[A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks](https://md.research.elamur.ai/free/en/papers/hashimoto-2016-joint-many-task-model-growing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kazuma Hashimoto, Caiming Xiong, Yoshimasa Tsuruoka, et al.*2016 · 674 citations*
5. **[Dissecting Contextual Word Embeddings: Architecture and Representation](https://md.research.elamur.ai/free/en/papers/peters-2018-dissecting-contextual-word-embeddings-architecture/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Matthew E. Peters, Mark Neumann, Luke Zettlemoyer, et al.*2018 · 592 citations*
6. **[An Analysis of Encoder Representations in Transformer-Based Machine Translation](https://md.research.elamur.ai/free/en/papers/raganato-2018-analysis-encoder-representations-transformer-based/) [EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/emnlp-workshop-blackboxnlp-analyzing-and-interpreting-neural-networks-for-nlp/)**Alessandro Raganato, Jörg Tiedemann*2018 · 369 citations*
7. [**UDPipe 2.0 Prototype at CoNLL 2018 UD Shared Task**Milan Straka*2018 · 303 citations*](https://md.research.elamur.ai/free/en/papers/straka-2018-udpipe-2-0-prototype-conll/)
8. **[Semantic Parsing for Task Oriented Dialog using Hierarchical Representations](https://md.research.elamur.ai/free/en/papers/gupta-2018-semantic-parsing-task-oriented-dialog/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sonal Gupta, Rushin Shah, Mrinal Mohit, et al.*2018 · 282 citations*
9. **[Head-Driven Phrase Structure Grammar Parsing on Penn Treebank](https://md.research.elamur.ai/free/en/papers/zhou-2019-head-driven-phrase-structure-grammar/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junru Zhou, Hai Zhao*2019 · 219 citations*
10. **[Learning to Parse and Translate Improves Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/eriguchi-2017-learning-parse-translate-improves-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Akiko Eriguchi, Yoshimasa Tsuruoka, Kyunghyun Cho*2017 · 217 citations*
11. **[LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better](https://md.research.elamur.ai/free/en/papers/kuncoro-2018-lstms-can-learn-syntax-sensitive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adhiguna Kuncoro, Chris Dyer, John Hale, et al.*2018 · 208 citations*
12. **[Learning Language Representations for Typology Prediction](https://md.research.elamur.ai/free/en/papers/malaviya-2017-learning-language-representations-typology-prediction/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chaitanya Malaviya, Graham Neubig, Patrick Littell*2017 · 187 citations*
13. **[Neural Discourse Structure for Text Categorization](https://md.research.elamur.ai/free/en/papers/ji-2017-neural-discourse-structure-text-categorization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yangfeng Ji, Noah A. Smith*2017 · 181 citations*
14. **[Generating Sentences from Disentangled Syntactic and Semantic Spaces](https://md.research.elamur.ai/free/en/papers/bao-2019-generating-sentences-disentangled-syntactic-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Bao, Hao Zhou, Shujian Huang, et al.*2019 · 154 citations*
15. **[Seq2seq Dependency Parsing](https://md.research.elamur.ai/free/en/papers/li-2018-seq2seq-dependency-parsing/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zuchao Li, Jiaxun Cai, Shexia He, et al.*2018 · 153 citations*
16. **[Scheduled Multi-Task Learning: From Syntax to Translation](https://md.research.elamur.ai/free/en/papers/kiperwasser-2018-scheduled-multi-task-learning-syntax/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Eliyahu Kiperwasser, Miguel Ballesteros*2018 · 130 citations*
17. **[In-Order Transition-based Constituent Parsing](https://md.research.elamur.ai/free/en/papers/liu-2017-order-transition-based-constituent-parsing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiangming Liu, Yue Zhang*2017 · 99 citations*
18. **[Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale](https://md.research.elamur.ai/free/en/papers/sartran-2022-transformer-grammars-augmenting-transformer-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Laurent Sartran, Samuel Barrett, Adhiguna Kuncoro, et al.*2022 · 72 citations*
19. **[Learning an Executable Neural Semantic Parser](https://md.research.elamur.ai/free/en/papers/cheng-2019-learning-executable-neural-semantic-parser/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Jianpeng Cheng, Siva Reddy, Vijay Saraswat, et al.*2019 · 63 citations*
20. **[Neural Generative Rhetorical Structure Parsing](https://md.research.elamur.ai/free/en/papers/mabona-2019-neural-generative-rhetorical-structure-parsing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Amandla Mabona, Laura Rimell, Stephen Clark, et al.*2019 · 36 citations*
21. **[A closer look at the performance of neural language models on reflexive anaphor licensing](https://md.research.elamur.ai/free/en/papers/hu-2020-closer-look-performance-neural-language/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Jennifer Hu, Sherry Yong Chen, Roger Levy*2020 · 24 citations*
22. [**Comparing Neural Network Parsers for a Less-resourced and Morphologically-rich Language: Amharic Dependency Parser**Binyam Ephrem Seyoum, Yusuke Miyao, Baye Yimam Mekonnen*2020 · 2 citations*](https://md.research.elamur.ai/free/en/papers/seyoum-2020-comparing-neural-network-parsers-less/)

51 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/kuncoro-2016-recurrent-neural-network-grammars-learn/) — What Do Recurrent Neural Network Grammars Learn About Syntax?