---
title: "Who cites Simple and Accurate Dependency Parsing Using…"
description: "288 papers of the Elamur Research library cite «Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations», found in their…"
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---
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# Who cites «Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations»

288 papers of our library cite it (of the 140,884 whose bibliographies we read) · 43 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/kiperwasser-2016-simple-accurate-dependency-parsing-bidirectional/)

1. [**Deep Biaffine Attention for Neural Dependency Parsing**Timothy Dozat, Christopher D. Manning*2016 · 1,320 citations*](https://md.research.elamur.ai/free/en/papers/dozat-2016-deep-biaffine-attention-neural-dependency/)
2. [**Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies**Tal Linzen, Emmanuel Dupoux, Yoav Goldberg*2016 · 1,239 citations*](https://md.research.elamur.ai/free/en/papers/linzen-2016-assessing-ability-lstms-learn-syntax/)
3. [**Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling**Diego Marcheggiani, Ivan Titov*2017 · 1,101 citations*](https://md.research.elamur.ai/free/en/papers/marcheggiani-2017-encoding-sentences-graph-convolutional-networks/)
4. [**Colorless Green Recurrent Networks Dream Hierarchically**Kristina Gulordava, Piotr Bojanowski, Edouard Grave, et al.*2018 · 759 citations*](https://md.research.elamur.ai/free/en/papers/gulordava-2018-colorless-green-recurrent-networks-dream/)
5. [**Analysis Methods in Neural Language Processing: A Survey**Yonatan Belinkov, James Glass*2019 · 735 citations*](https://md.research.elamur.ai/free/en/papers/belinkov-2019-analysis-methods-neural-language-processing/)
6. [**ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing**Mark Neumann, Daniel King, Iz Beltagy, et al.*2019 · 674 citations*](https://md.research.elamur.ai/free/en/papers/neumann-2019-scispacy-fast-robust-models-biomedical/)
7. [**Linguistically-Informed Self-Attention for Semantic Role Labeling**Emma Strubell, Patrick Verga, Daniel Andor, et al.*2018 · 598 citations*](https://md.research.elamur.ai/free/en/papers/strubell-2018-linguistically-informed-self-attention-semantic/)
8. [**DyNet: The Dynamic Neural Network Toolkit**Graham Neubig, Chris Dyer, Yoav Goldberg, et al.*2017 · 485 citations*](https://md.research.elamur.ai/free/en/papers/neubig-2017-dynet-dynamic-neural-network-toolkit/)
9. [**A Minimal Span-Based Neural Constituency Parser**Mitchell Stern, Jacob Andreas, Dan Klein*2017 · 309 citations*](https://md.research.elamur.ai/free/en/papers/stern-2017-minimal-span-based-neural-constituency/)
10. [**Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing**Tal Schuster, Ori Ram, Regina Barzilay, et al.*2019 · 294 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2019-cross-lingual-alignment-contextual-word/)
11. [**Neural End-to-End Learning for Computational Argumentation Mining**Steffen Eger, Johannes Daxenberger, Iryna Gurevych*2017 · 263 citations*](https://md.research.elamur.ai/free/en/papers/eger-2017-neural-end-end-learning-computational/)
12. [**Multilingual is not enough: BERT for Finnish**Antti Virtanen, Jenna Kanerva, Rami Ilo, et al.*2019 · 256 citations*](https://md.research.elamur.ai/free/en/papers/virtanen-2019-multilingual-enough-bert-finnish/)
13. [**Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss**Barbara Plank, Anders Søgaard, Yoav Goldberg*2016 · 201 citations*](https://md.research.elamur.ai/free/en/papers/plank-2016-multilingual-part-speech-tagging-bidirectional/)
14. [**Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic Oracles**James Cross, Liang Huang*2016 · 191 citations*](https://md.research.elamur.ai/free/en/papers/cross-2016-span-based-constituency-parsing-structure/)
15. [**Efficient Second-Order TreeCRF for Neural Dependency Parsing**Yu Zhang, Zhenghua Li, Min Zhang*2020 · 145 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2020-efficient-second-order-treecrf-neural/)
16. [**Scheduled Multi-Task Learning: From Syntax to Translation**Eliyahu Kiperwasser, Miguel Ballesteros*2018 · 130 citations*](https://md.research.elamur.ai/free/en/papers/kiperwasser-2018-scheduled-multi-task-learning-syntax/)
17. [**Annotation, Modelling and Analysis of Fine-Grained Emotions on a Stance and Sentiment Detection Corpus**Hendrik Schuff, Jeremy Barnes, Julian Mohme, et al.*2017 · 129 citations*](https://md.research.elamur.ai/free/en/papers/schuff-2017-annotation-modelling-analysis-fine-grained/)
18. [**Parsing Tweets into Universal Dependencies**Yijia Liu, Yi Zhu, Wanxiang Che, et al.*2018 · 121 citations*](https://md.research.elamur.ai/free/en/papers/liu-2018-parsing-tweets-into-universal-dependencies/)
19. [**In-Order Transition-based Constituent Parsing**Jiangming Liu, Yue Zhang*2017 · 98 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-order-transition-based-constituent-parsing/)
20. [**A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling**Diego Marcheggiani, Anton Frolov, Ivan Titov*2017 · 86 citations*](https://md.research.elamur.ai/free/en/papers/marcheggiani-2017-simple-accurate-syntax-agnostic-neural/)
21. [**Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples**Xiaoqing Zheng, Jiehang Zeng, Yi Zhou, et al.*2020 · 54 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2020-evaluating-enhancing-robustness-neural-network/)
22. [**Universal Dependencies Parsing for Colloquial Singaporean English**Hongmin Wang, Yue Zhang, GuangYong Leonard Chan, et al.*2017 · 49 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-universal-dependencies-parsing-colloquial-singaporean/)
23. [**Learning Contextually Informed Representations for Linear-Time Discourse Parsing**Yang Liu, Mirella Lapata*2017 · 44 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-learning-contextually-informed-representations-linear/)
24. [**Arc-swift: A Novel Transition System for Dependency Parsing**Peng Qi, Christopher D. Manning*2017 · 39 citations*](https://md.research.elamur.ai/free/en/papers/qi-2017-arc-swift-novel-transition-system/)
25. [**Graph-to-Graph Transformer for Transition-based Dependency Parsing**Alireza Mohammadshahi, James Henderson*2020 · 23 citations*](https://md.research.elamur.ai/free/en/papers/mohammadshahi-2020-graph-graph-transformer-transition-based/)
26. [**Applying Occam's Razor to Transformer-Based Dependency Parsing: What Works, What Doesn't, and What is Really Necessary**Stefan Grünewald, Annemarie Friedrich, Jonas Kuhn*2021 · 18 citations*](https://md.research.elamur.ai/free/en/papers/grunewald-2021-applying-occam-s-razor-transformer/)
27. [**Hexatagging: Projective Dependency Parsing as Tagging**Afra Amini, Tianyu Liu, Ryan Cotterell*2023 · 16 citations*](https://md.research.elamur.ai/free/en/papers/amini-2023-hexatagging-projective-dependency-parsing-as/)
28. [**A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021**Mark Anderson, Carlos Gómez-Rodríguez*2021 · 10 citations*](https://md.research.elamur.ai/free/en/papers/anderson-2021-modest-pareto-optimisation-analysis-dependency/)
29. [**Using Modern Languages to Parse Ancient Ones: a Test on Old English**Luca Brigada Villa, Martina Giarda*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/villa-2023-modern-languages-parse-ancient-ones/)
30. [**Nucleus Composition in Transition-based Dependency Parsing**Joakim Nivre, Ali Basirat, Luise Dürlich, et al.*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/nivre-2022-nucleus-composition-transition-based-dependency/)
31. [**Improving a Strong Neural Parser with Conjunction-Specific Features**Jessica Ficler, Yoav Goldberg*2017 · 9 citations*](https://md.research.elamur.ai/free/en/papers/ficler-2017-improving-strong-neural-parser-conjunction/)
32. [**MRL Parsing Without Tears: The Case of Hebrew**Shaltiel Shmidman, Avi Shmidman, Moshe Koppel, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2024-mrl-parsing-without-tears-case/)
33. [**Integrating Graph-Based and Transition-Based Dependency Parsers in the Deep Contextualized Era**Agnieszka Falenska, Anders Björkelund, Jonas Kuhn*2020 · 8 citations*](https://md.research.elamur.ai/free/en/papers/falenska-2020-integrating-graph-based-transition-based/)
34. [**A Truly Joint Neural Architecture for Segmentation and Parsing**Danit Yshaayahu Levi, Reut Tsarfaty*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/levi-2024-truly-joint-neural-architecture-segmentation/)
35. [**Fast and Accurate Non-Projective Dependency Tree Linearization**Xiang Yu, Simon Tannert, Ngoc Thang Vu, et al.*2020 · 7 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-fast-accurate-non-projective-dependency/)
36. [**Cross-lingual Semantic Representation for NLP with UCCA**Omri Abend, Dotan Dvir, Daniel Hershcovich, et al.*2020 · 6 citations*](https://md.research.elamur.ai/free/en/papers/abend-2020-cross-lingual-semantic-representation-nlp/)
37. [**Approximate Dynamic Oracle for Dependency Parsing with Reinforcement Learning**Xiang Yu, Ngoc Thang Vu, Jonas Kuhn*2018 · 5 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-approximate-dynamic-oracle-dependency-parsing/)
38. [**The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task**James Barry, Alireza Mohammadshahi, Joachim Wagner, et al.*2021 · 4 citations*](https://md.research.elamur.ai/free/en/papers/barry-2021-dcu-epfl-enhanced-dependency-parser/)
39. [**Extracting Headless MWEs from Dependency Parse Trees: Parsing, Tagging, and Joint Modeling Approaches**Tianze Shi, Lillian Lee*2020 · 3 citations*](https://md.research.elamur.ai/free/en/papers/shi-2020-extracting-headless-mwes-dependency-parse/)
40. [**Evaluating Universal Dependency Parser Recovery of Predicate Argument Structure via CompChain Analysis**Sagar Indurkhya, Beracah Yankama, Robert C. Berwick*2021 · 2 citations*](https://md.research.elamur.ai/free/en/papers/indurkhya-2021-evaluating-universal-dependency-parser-recovery/)
41. [**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/)
42. [**Transition-based Bubble Parsing: Improvements on Coordination Structure Prediction**Tianze Shi, Lillian Lee*2021*](https://md.research.elamur.ai/free/en/papers/shi-2021-transition-based-bubble-parsing-improvements/)
43. [**Recursive LSTM Tree Representation for Arc-Standard Transition-Based Dependency Parsing**Mohab Elkaref, Bernd Bohnet*2019*](https://md.research.elamur.ai/free/en/papers/elkaref-2019-recursive-lstm-tree-representation-arc/)

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

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