---
title: "Who cites Transition-Based Dependency Parsing with Stack…"
description: "The papers of the Elamur Research library that cite «Transition-Based Dependency Parsing with Stack Long Short-Term Memory», found in their bibliographies."
canonical: "https://research.elamur.ai/free/en/papers/missing-2015-dyer-transition-based-dependency-parsing-stack/cited-by/page/3/"
---
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# Who cites «Transition-Based Dependency Parsing with Stack Long Short-Term Memory» · page 3

304 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.research.elamur.ai/free/en/papers/missing-2015-dyer-transition-based-dependency-parsing-stack/)

Pages: [1](https://md.research.elamur.ai/free/en/papers/missing-2015-dyer-transition-based-dependency-parsing-stack/cited-by/) · [2](https://md.research.elamur.ai/free/en/papers/missing-2015-dyer-transition-based-dependency-parsing-stack/cited-by/page/2/) · **3** · [4](https://md.research.elamur.ai/free/en/papers/missing-2015-dyer-transition-based-dependency-parsing-stack/cited-by/page/4/)

1. [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)*
2. [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)*
3. [Prepositional Phrase Attachment over Word Embedding Products](https://md.research.elamur.ai/free/en/papers/lingbulk-2017-madhyastha-prepositional-phrase-attachment-over-word/) *— our card · 2017 · Proceedings of the 15th International Conference on Parsing Technologies*
4. [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)*
5. [Shift-Reduce Constituent Parsing with Neural Lookahead Features](https://aclanthology.org/Q17-1004/) *— 2017 · Transactions of the Association for Computational Linguistics*
6. [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*
7. [Survey: Multiword Expression Processing: A Survey](https://aclanthology.org/J17-4005/) *— 2017*
8. [TAG Parser Evaluation using Textual Entailments](https://aclanthology.org/W17-6214/) *— 2017 · Proceedings of the 13th International Workshop on Tree Adjoining Grammars and Related Formalisms*
9. [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*
10. [The HIT-SCIR System for End-to-End Parsing of Universal Dependencies](https://aclanthology.org/K17-3005/) *— 2017 · Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies*
11. [Towards Neural Machine Translation with Latent Tree Attention](https://aclanthology.org/W17-4303/) *— 2017 · Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing*
12. [Transition-Based Disfluency Detection using LSTMs](https://aclanthology.org/D17-1296/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
13. [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*
14. [Universal Dependencies Parsing for Colloquial Singaporean English](https://md.research.elamur.ai/free/en/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)*
15. [Word vectors, reuse, and replicability: Towards a community repository of large-text resources](https://aclanthology.org/W17-0237/) *— 2017 · Proceedings of the 21st Nordic Conference on Computational Linguistics*
16. [A Convolutional Attention Network for Extreme Summarization of Source Code](https://arxiv.org/abs/1602.03001) *— 2016 · arXiv:1602.03001*
17. [A Fast Unified Model for Parsing and Sentence Understanding](https://aclanthology.org/P16-1139/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
18. [A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks](https://arxiv.org/abs/1611.01587) *— 2016 · arXiv:1611.01587*
19. [A Latent Variable Recurrent Neural Network for Discourse-Driven Language Models](https://aclanthology.org/N16-1037/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
20. [A Long Short-Term Memory Framework for Predicting Humor in Dialogues](https://aclanthology.org/N16-1016/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
21. [A Neural Attention Model for Disfluency Detection](https://aclanthology.org/C16-1027/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
22. [A Neural Network Architecture for Multilingual Punctuation Generation](https://aclanthology.org/D16-1111/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
23. [A Search-Based Dynamic Reranking Model for Dependency Parsing](https://aclanthology.org/P16-1132/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
24. [A Universal Framework for Inductive Transfer Parsing across Multi-typed Treebanks](https://aclanthology.org/C16-1002/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
25. [An empirical study for Vietnamese dependency parsing](https://aclanthology.org/U16-1017/) *— 2016 · Proceedings of the Australasian Language Technology Association Workshop 2016*
26. [Bi-directional Attention with Agreement for Dependency Parsing](https://aclanthology.org/D16-1238/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
27. [Bidirectional LSTM for Named Entity Recognition in Twitter Messages](https://aclanthology.org/W16-3920/) *— 2016 · Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)*
28. [Capturing Pragmatic Knowledge in Article Usage Prediction using LSTMs](https://aclanthology.org/C16-1247/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
29. [CharNER: Character-Level Named Entity Recognition](https://aclanthology.org/C16-1087/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
30. [Composing Distributed Representations of Relational Patterns](https://aclanthology.org/P16-1215/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
31. [Context-Sensitive Lexicon Features for Neural Sentiment Analysis](https://aclanthology.org/D16-1169/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
32. [Data Recombination for Neural Semantic Parsing](https://aclanthology.org/P16-1002/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
33. [Deep Biaffine Attention for Neural Dependency Parsing](https://md.research.elamur.ai/free/en/papers/missing-2016-dozat-deep-biaffine-attention-neural-dependency/) *— our card · 2016 · arXiv:1611.01734*
34. [Differentia compositionem facit. A Slower-Paced and Reliable Parser for Latin](https://aclanthology.org/L16-1108/) *— 2016 · Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)*
35. [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*
36. [Domainless Adaptation by Constrained Decoding on a Schema Lattice](https://aclanthology.org/C16-1193/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
37. [Easy-First Dependency Parsing with Hierarchical Tree LSTMs](https://aclanthology.org/Q16-1032/) *— 2016*
38. [End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF](https://arxiv.org/abs/1603.01354) *— 2016 · arXiv:1603.01354*
39. [Expectation-Regulated Neural Model for Event Mention Extraction](https://aclanthology.org/N16-1045/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
40. [Expected F-Measure Training for Shift-Reduce Parsing with Recurrent Neural Networks](https://aclanthology.org/N16-1025/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
41. [Exploiting Mutual Benefits between Syntax and Semantic Roles using Neural Network](https://aclanthology.org/D16-1098/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
42. [Frustratingly Easy Neural Domain Adaptation](https://aclanthology.org/C16-1038/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
43. [Global Neural CCG Parsing with Optimality Guarantees](https://aclanthology.org/D16-1262/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
44. [Globally Normalized Transition-Based Neural Networks](https://aclanthology.org/P16-1231/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
45. [Graph-based Dependency Parsing with Bidirectional LSTM](https://aclanthology.org/P16-1218/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
46. [Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs](https://aclanthology.org/K16-1019/) *— 2016 · Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning*
47. [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)*
48. [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*
49. [LSTM CCG Parsing](https://md.research.elamur.ai/free/en/papers/aclbulk-2016-lewis-lstm-ccg-parsing/) *— our card · 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
50. [LSTM Shift-Reduce CCG Parsing](https://aclanthology.org/D16-1181/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
51. [Learning Continuous Semantic Representations of Symbolic Expressions](https://arxiv.org/abs/1611.01423) *— 2016 · arXiv:1611.01423*
52. [Learning Crosslingual Word Embeddings without Bilingual Corpora](https://aclanthology.org/D16-1136/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
53. [Learning Distributed Word Representations For Bidirectional LSTM Recurrent Neural Network](https://aclanthology.org/N16-1064/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
54. [Learning Global Features for Coreference Resolution](https://aclanthology.org/N16-1114/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
55. [Learning Orthographic Features in Bi-directional LSTM for Biomedical Named Entity Recognition](https://aclanthology.org/W16-5102/) *— 2016 · Proceedings of the Fifth Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM2016)*
56. [Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning](https://aclanthology.org/P16-1013/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
57. [Learning to recognise named entities in tweets by exploiting weakly labelled data](https://aclanthology.org/W16-3921/) *— 2016 · Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)*
58. [Long Short-Term Memory-Networks for Machine Reading](https://aclanthology.org/D16-1053/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
59. [Making Dependency Labeling Simple, Fast and Accurate](https://aclanthology.org/N16-1126/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
60. [Many Languages, One Parser](https://aclanthology.org/Q16-1031/) *— 2016 · Transactions of the Association for Computational Linguistics*
61. [Mapping Unseen Words to Task-Trained Embedding Spaces](https://aclanthology.org/W16-1612/) *— 2016 · Proceedings of the 1st Workshop on Representation Learning for NLP*
62. [Massively Multilingual Word Embeddings](https://arxiv.org/abs/1602.01925) *— 2016 · arXiv:1602.01925*
63. [Measuring the Information Content of Financial News](https://aclanthology.org/C16-1303/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
64. [Neural Architectures for Named Entity Recognition](https://aclanthology.org/N16-1030/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
65. [Neural Network-Based Model for Japanese Predicate Argument Structure Analysis](https://aclanthology.org/P16-1117/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
66. [Neural Scoring Function for MST Parser](https://aclanthology.org/L16-1110/) *— 2016 · Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)*
67. [Neural Shift-Reduce CCG Semantic Parsing](https://aclanthology.org/D16-1183/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
68. [Optimizing Performance of Recurrent Neural Networks on GPUs](https://arxiv.org/abs/1604.01946) *— 2016 · arXiv:1604.01946*
69. [Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning](https://aclanthology.org/N16-1161/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
70. [Probabilistic Graph-based Dependency Parsing with Convolutional Neural Network](https://aclanthology.org/P16-1131/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
71. [Prédiction structurée pour l”analyse syntaxique en constituants par transitions : modèles denses et modèles creux Structured Prediction for Transition-based Constituent Parsing: Dense and Sparse Models](https://aclanthology.org/2016.tal-1.3/) *— 2016*
72. [Recurrent Dropout without Memory Loss](https://aclanthology.org/C16-1165/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
73. [Recurrent Memory Networks for Language Modeling](https://aclanthology.org/N16-1036/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
74. [Recurrent Neural Network Grammars](https://aclanthology.org/N16-1024/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
75. [Right-truncatable Neural Word Embeddings](https://aclanthology.org/N16-1135/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
76. [Shift-Reduce CCG Parsing using Neural Network Models](https://aclanthology.org/N16-1052/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
77. [Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations](https://md.research.elamur.ai/free/en/papers/narrative-2016-kiperwasser-simple-accurate-dependency-parsing-bidirectional/) *— our card · 2016*
78. [Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic Oracles](https://arxiv.org/abs/1612.06475) *— 2016 · arXiv:1612.06475*
79. [Stack-propagation: Improved Representation Learning for Syntax](https://aclanthology.org/P16-1147/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
80. [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*
81. [Top-down Tree Long Short-Term Memory Networks](https://aclanthology.org/N16-1035/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
82. [Training with Exploration Improves a Greedy Stack LSTM Parser](https://aclanthology.org/D16-1211/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
83. [Transition-Based Dependency Parsing with Heuristic Backtracking](https://aclanthology.org/D16-1254/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
84. [Transition-Based Neural Word Segmentation](https://aclanthology.org/P16-1040/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
85. [Transition-based dependency parsing with topological fields](https://aclanthology.org/P16-2001/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
86. [Weighting Finite-State Transductions With Neural Context](https://aclanthology.org/N16-1076/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
87. [Which argument is more convincing? Analyzing and predicting convincingness of Web arguments using bidirectional LSTM](https://aclanthology.org/P16-1150/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
88. [A Bayesian Model for Generative Transition-based Dependency Parsing](https://aclanthology.org/W15-2108/) *— 2015 · Proceedings of the Third International Conference on Dependency Linguistics (Depling 2015)*
89. [A Neural Probabilistic Structured-Prediction Model for Transition-Based Dependency Parsing](https://aclanthology.org/P15-1117/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
90. [A Primer on Neural Network Models for Natural Language Processing](https://arxiv.org/abs/1510.00726) *— 2015 · arXiv:1510.00726*
91. [An Improved Non-monotonic Transition System for Dependency Parsing](https://md.research.elamur.ai/free/en/papers/missing-2015-honnibal-improved-non-monotonic-transition-system/) *— our card · 2015 · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing*
92. [Combining Discrete and Continuous Features for Deterministic Transition-based Dependency Parsing](https://aclanthology.org/D15-1153/) *— 2015 · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing*
93. [Generative Incremental Dependency Parsing with Neural Networks](https://aclanthology.org/P15-2142/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
94. [Improved Transition-Based Parsing and Tagging with Neural Networks](https://aclanthology.org/D15-1159/) *— 2015 · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing*
95. [Improved Transition-based Parsing by Modeling Characters instead of Words with LSTMs](https://aclanthology.org/D15-1041/) *— 2015 · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing*
96. [Learning to Transduce with Unbounded Memory](https://arxiv.org/abs/1506.02516) *— 2015 · arXiv:1506.02516*
97. [Reducing Lexical Features in Parsing by Word Embeddings](https://aclanthology.org/Y15-1013/) *— 2015 · Proceedings of the 29th Pacific Asia Conference on Language, Information and Computation*
98. [Semi-supervised Dependency Parsing using Bilexical Contextual Features from Auto-Parsed Data](https://aclanthology.org/D15-1158/) *— 2015 · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing*
99. [Structured Training for Neural Network Transition-Based Parsing](https://aclanthology.org/P15-1032/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
100. [The Goldilocks Principle: Reading Children”s Books with Explicit Memory Representations](https://arxiv.org/abs/1511.02301) *— 2015 · arXiv:1511.02301*

Pages: [1](https://md.research.elamur.ai/free/en/papers/missing-2015-dyer-transition-based-dependency-parsing-stack/cited-by/) · [2](https://md.research.elamur.ai/free/en/papers/missing-2015-dyer-transition-based-dependency-parsing-stack/cited-by/page/2/) · **3** · [4](https://md.research.elamur.ai/free/en/papers/missing-2015-dyer-transition-based-dependency-parsing-stack/cited-by/page/4/)