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# Who cites «Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations» · page 3

288 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/narrative-2016-kiperwasser-simple-accurate-dependency-parsing-bidirectional/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/narrative-2016-kiperwasser-simple-accurate-dependency-parsing-bidirectional/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/narrative-2016-kiperwasser-simple-accurate-dependency-parsing-bidirectional-2/) · **3**

1. [From Raw Text to Universal Dependencies - Look, No Tags!](https://aclanthology.org/K17-3022/) *— 2017 · Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies*
2. [Improving a Strong Neural Parser with Conjunction-Specific Features](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2017-ficler-improving-strong-neural-parser-conjunction/) *— our card · 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers*
3. [In-Order Transition-based Constituent Parsing](https://aclanthology.org/Q17-1029/) *— 2017 · Transactions of the Association for Computational Linguistics*
4. [Incremental Discontinuous Phrase Structure Parsing with the GAP Transition](https://aclanthology.org/E17-1118/) *— 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers*
5. [Incremental Graph-based Neural Dependency Parsing](https://aclanthology.org/D17-1173/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
6. [Learning Contextually Informed Representations for Linear-Time Discourse Parsing](https://aclanthology.org/D17-1133/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
7. [Learning What''s Easy: Fully Differentiable Neural Easy-First Taggers](https://aclanthology.org/D17-1036/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
8. [Learning to select data for transfer learning with Bayesian Optimization](https://aclanthology.org/D17-1038/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
9. [Leveraging Newswire Treebanks for Parsing Conversational Data with Argument Scrambling](https://aclanthology.org/W17-6309/) *— 2017 · Proceedings of the 15th International Conference on Parsing Technologies*
10. [Multi-task Domain Adaptation for Sequence Tagging](https://aclanthology.org/W17-2612/) *— 2017 · Proceedings of the 2nd Workshop on Representation Learning for NLP*
11. [Multilingual Lexicalized Constituency Parsing with Word-Level Auxiliary Tasks](https://aclanthology.org/E17-2053/) *— 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers*
12. [Neural End-to-End Learning for Computational Argumentation Mining](https://aclanthology.org/P17-1002/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
13. [Neural Joint Model for Transition-based Chinese Syntactic Analysis](https://aclanthology.org/P17-1111/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
14. [Neural Probabilistic Model for Non-projective MST Parsing](https://aclanthology.org/I17-1007/) *— 2017 · Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
15. [Reconstruction of Word Embeddings from Sub-Word Parameters](https://aclanthology.org/W17-4119/) *— 2017 · Proceedings of the First Workshop on Subword and Character Level Models in NLP*
16. [Représentation et analyse automatique des discontinuités syntaxiques dans les corpus arborés en constituants du français (Representation and parsing of syntactic discontinuities in French constituent treebanks)](https://aclanthology.org/2017.jeptalnrecital-long.6/) *— 2017 · Actes des 24ème Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 - Articles longs*
17. [Robust Incremental Neural Semantic Graph Parsing](https://aclanthology.org/P17-1112/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
18. [Stack-based Multi-layer Attention for Transition-based Dependency Parsing](https://aclanthology.org/D17-1175/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
19. [Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency Parsing](https://aclanthology.org/E17-1064/) *— 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers*
20. [UParse: the Edinburgh system for the CoNLL 2017 UD shared task](https://aclanthology.org/K17-3010/) *— 2017 · Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies*
21. [Universal Dependencies Parsing for Colloquial Singaporean English](https://md.mova.elamur.ai/free/en/docs/papers/ud-2017-wang-universal-dependencies-parsing-colloquial-singaporean/) *— our card · 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
22. [Universal Semantic Parsing](https://aclanthology.org/D17-1009/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
23. [An empirical study for Vietnamese dependency parsing](https://aclanthology.org/U16-1017/) *— 2016 · Proceedings of the Australasian Language Technology Association Workshop 2016*
24. [Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies](https://aclanthology.org/Q16-1037/) *— 2016*
25. [Challenges of Computational Processing of Code-Switching](https://aclanthology.org/W16-5801/) *— 2016 · Proceedings of the Second Workshop on Computational Approaches to Code Switching*
26. [Deep Biaffine Attention for Neural Dependency Parsing](https://md.mova.elamur.ai/free/en/docs/papers/missing-2016-dozat-deep-biaffine-attention-neural-dependency/) *— our card · 2016 · arXiv:1611.01734*
27. [Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser](https://aclanthology.org/D16-1180/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
28. [Incremental Parsing with Minimal Features Using Bi-Directional LSTM](https://aclanthology.org/P16-2006/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
29. [Keystroke dynamics as signal for shallow syntactic parsing](https://aclanthology.org/C16-1059/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
30. [Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss](https://arxiv.org/abs/1604.05529) *— 2016 · arXiv:1604.05529*
31. [Neural Shift-Reduce CCG Semantic Parsing](https://aclanthology.org/D16-1183/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
32. [Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic Oracles](https://arxiv.org/abs/1612.06475) *— 2016 · arXiv:1612.06475*
33. [The SIGMORPHON 2016 Shared Task–-Morphological Reinflection](https://aclanthology.org/W16-2002/) *— 2016 · Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology*
34. [What Do Recurrent Neural Network Grammars Learn About Syntax?](https://arxiv.org/abs/1611.05774) *— 2016 · arXiv:1611.05774*
35. agrawal-2020-eyes-parse-gaze-features-syntactic
36. akermi-2021-generation-automatique-de-texte-en
37. an-2023-tibetan-dependency-parsing-graph-convolutional
38. antonelli-2018-parsing-italian-texts-together-is
39. ballesteros-2017-arc-standard-spinal-parsing-stack
40. banerjee-2025-hits-disrpt-2025-discourse-segmentation
41. barnabo-2023-supervised-clustering-loss-clustering-friendly
42. benton-2021-cross-register-projection-headline-part
43. buljan-2020-tale-three-parsers-diagnostic-evaluation
44. chen-2022-mt-speech-semeval-2022-task
45. cole-2021-graph-based-decoding-task-oriented
46. doan-2020-joint-deep-contextualized-word-representation
47. doitch-2019-perturbation-based-learning-structured-nlp
48. eecke-2022-neural-heuristics-scaling-constructional-language
49. fischer-2019-association-metrics-neural-transition-based
50. floquet-2025-scaling-graph-based-dependency-parsing
51. go-2024-is-there-gender-bias-dependency
52. grunewald-2018-generalized-chart-constraints-efficient-pcfg
53. hildebrand-2020-recognizing-sentence-level-logical-document
54. ji-2021-unified-encoding-structures-transition-systems
55. jindal-2020-clar-cross-lingual-argument-regularizer
56. joshi-2025-dependency-parsing-based-syntactic-enhancement
57. kasai-2019-jabberwocky-parsing-dependency-parsing-lexical
58. kohita-2018-dynamic-feature-selection-attention-incremental
59. kurtz-2019-interplay-between-loss-functions-structural
60. lhoneux-2020-what-should-do-can-lstms
61. li-2019-generative-model-punctuation-dependency-trees
62. li-2020-joint-model-graph-based-chinese
63. li-2021-apgn-adversarial-parameter-generation-networks
64. li-2022-semi-supervised-domain-adaptation-dependency
65. li-2025-implicit-word-reordering-knowledge-distillation
66. liu-2023-linear-time-modeling-linguistic-structure
67. malca-2018-neural-transition-based-parsing-web
68. matsuno-2018-reduction-parameter-redundancy-biaffine-classifiers
69. nallani-2020-simple-effective-dependency-parser-telugu
70. ortiz-2023-assessment-pre-trained-models-across
71. prange-2023-empirical-sufficiency-lower-bounds-language
72. ren-2018-building-ellipsis-aware-chinese-dependency
73. saied-2019-comparing-linear-neural-models-competitive
74. schluter-2019-recurrent-models-lower-bounds-projective
75. shadikhodjaev-2019-cbnu-system-sigmorphon-2019-shared
76. stanojevic-2017-neural-discontinuous-constituency-parsing
77. stymne-2017-bilstm-based-system-cross-lingual
78. stymne-2023-parser-evaluation-analyzing-swedish-19th
79. szabo-2020-quasi-multitask-learning-efficient-surrogate
80. talmina-2020-neural-network-learning-russian-genitive
81. thien-2020-applying-graph-neural-networks-vietnamese
82. tuc-2020-self-attended-stack-pointer-networks
83. ustun-2019-multi-team-multi-attention-multi
84. vania-2018-explicitly-modeling-case-improves-neural
85. wang-2020-semi-supervised-dependency-parsing-arc
86. xu-2022-multi-layer-pseudo-siamese-biaffine
87. zhang-2020-semi-supervised-autoencoding-projective-dependency
88. zhang-2022-sharp-search-based-adversarial-attack

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