---
title: "Chris Dyer — all works — Elamur Research"
description: "All 76 works of Chris Dyer in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/chris-dyer/works/"
---
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# Chris Dyer — all works

76 works · [← Chris Dyer](https://md.research.elamur.ai/free/en/authors/chris-dyer/)

1. **[Moses: Open Source Toolkit for Statistical Machine Translation ↗](https://aclanthology.org/P07-2045/) Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions · no summary yet**Philipp Koehn et al.*2007 · 7,797 citations*
2. **[Hierarchical Attention Networks for Document Classification](https://md.research.elamur.ai/free/en/papers/yang-2016-hierarchical-attention-networks-document-classification/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zichao Yang, Diyi Yang, Chris Dyer, et al.*2016 · 5,436 citations*
3. **[Neural Architectures for Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/lample-2016-neural-architectures-named-entity-recognition/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, et al.*2016 · 5,319 citations*
4. [**The NarrativeQA Reading Comprehension Challenge**Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom, et al.*English · 1,042 citations*](https://md.research.elamur.ai/free/en/papers/kocisky-2018-narrativeqa-reading-comprehension-challenge/)
5. **[Scaling Language Models: Methods, Analysis & Insights from Training Gopher ↗](https://arxiv.org/abs/2112.11446) arXiv:2112.11446 · no summary yet**Jack W. Rae et al.*2021 · 928 citations*
6. [**Transition-Based Dependency Parsing with Stack Long Short-Term Memory**Chris Dyer, Miguel Ballesteros, Wang Ling, et al.*English · 868 citations*](https://md.research.elamur.ai/free/en/papers/dyer-2015-transition-based-dependency-parsing-stack/)
7. **[Improving Vector Space Word Representations Using Multilingual Correlation](https://md.research.elamur.ai/free/en/papers/faruqui-2014-improving-vector-space-word-representations/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Manaal Faruqui, Chris Dyer*2014 · 826 citations*
8. **[Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems ↗](https://aclanthology.org/P17-1015/) Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Wang Ling et al.*2017 · 810 citations*
9. **[Recurrent Neural Network Grammars ↗](https://aclanthology.org/N16-1024/) Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Chris Dyer et al.*2016 · 770 citations*
10. **[A Discriminative Graph-Based Parser for the Abstract Meaning Representation](https://md.research.elamur.ai/free/en/papers/flanigan-2014-discriminative-graph-based-parser-abstract/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jeffrey Flanigan, Sam Thomson, Jaime Carbonell, et al.*2014 · 508 citations*
11. **[Two/Too Simple Adaptations of Word2Vec for Syntax Problems](https://md.research.elamur.ai/free/en/papers/ling-2015-two-too-simple-adaptations-word2vec/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Wang Ling, Chris Dyer, Alan W. Black, et al.*2015 · 504 citations*
12. [**DyNet: The Dynamic Neural Network Toolkit arXiv:1701.03980**Graham Neubig, Chris Dyer, Yoav Goldberg, et al.*2017 · 489 citations*](https://md.research.elamur.ai/free/en/papers/neubig-2017-dynet-dynamic-neural-network-toolkit/)
13. **[Learning Deep Generative Models of Graphs ↗](https://arxiv.org/abs/1803.03324) arXiv (Cornell University) · no summary yet**Yujia Li et al.*2018 · 422 citations*
14. [**Massively Multilingual Word Embeddings arXiv:1602.01925**Waleed Ammar, George Mulcaire, Yulia Tsvetkov, et al.*2016 · 404 citations*](https://md.research.elamur.ai/free/en/papers/ammar-2016-massively-multilingual-word-embeddings/)
15. **[Improved Transition-based Parsing by Modeling Characters instead of Words with LSTMs](https://md.research.elamur.ai/free/en/papers/ballesteros-2015-improved-transition-based-parsing-modeling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Miguel Ballesteros, Chris Dyer, Noah A. Smith*2015 · 403 citations*
16. **[Many Languages, One Parser](https://md.research.elamur.ai/free/en/papers/ammar-2016-many-languages-one-parser/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Waleed Ammar, George Mulcaire, Miguel Ballesteros, et al.*2016 · 382 citations*
17. **[cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models](https://md.research.elamur.ai/free/en/papers/dyer-2010-cdec-decoder-alignment-learning-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chris Dyer, Adam Lopez, Juri Ganitkevitch, et al.*2010 · 374 citations*
18. **[Metaphor Detection with Cross-Lingual Model Transfer](https://md.research.elamur.ai/free/en/papers/tsvetkov-2014-metaphor-detection-cross-lingual-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulia Tsvetkov, Leonid Boytsov, Anatole Gershman, et al.*2014 · 371 citations*
19. **[Problems With Evaluation of Word Embeddings Using Word Similarity Tasks](https://md.research.elamur.ai/free/en/papers/faruqui-2016-problems-evaluation-word-embeddings-word/) [Workshop on Evaluating Vector Space Representations for NLP](https://md.research.elamur.ai/free/en/venues/workshop-on-evaluating-vector-space-representations-for-nlp/)**Manaal Faruqui, Yulia Tsvetkov, Pushpendre Rastogi, et al.*2016 · 334 citations*
20. [**Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation arXiv:1508.02096**Wang Ling, Tiago Luis, Luis Marujo, et al.*2015 · 308 citations*](https://md.research.elamur.ai/free/en/papers/ling-2015-finding-function-form-compositional-character/)
21. [**A Dependency Parser for Tweets**Lingpeng Kong, Nathan Schneider, Swabha Swayamdipta, et al.*English · 298 citations*](https://md.research.elamur.ai/free/en/papers/kong-2014-dependency-parser-tweets/)
22. **[Humor Recognition and Humor Anchor Extraction](https://md.research.elamur.ai/free/en/papers/yang-2015-humor-recognition-humor-anchor-extraction/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Diyi Yang, Alon Lavie, Chris Dyer, et al.*2015 · 265 citations*
23. [**Learning and Evaluating General Linguistic Intelligence arXiv:1901.11373**Dani Yogatama, Cyprien de Masson d'Autume, Jerome Connor, et al.*2019 · 248 citations*](https://md.research.elamur.ai/free/en/papers/yogatama-2019-learning-evaluating-general-linguistic-intelligence/)
24. **[Cross-lingual Models of Word Embeddings: An Empirical Comparison](https://md.research.elamur.ai/free/en/papers/upadhyay-2016-cross-lingual-models-word-embeddings/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shyam Upadhyay, Manaal Faruqui, Chris Dyer, et al.*2016 · 247 citations*
25. **[Improved Part-of-Speech Tagging for Online Conversational Text with Word Clusters](https://md.research.elamur.ai/free/en/papers/owoputi-2013-improved-part-speech-tagging-online/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Olutobi Owoputi, Brendan O'Connor, Chris Dyer, et al.*2013 · 247 citations*
26. **[Incorporating Structural Alignment Biases into an Attentional Neural Translation Model](https://md.research.elamur.ai/free/en/papers/cohn-2016-incorporating-structural-alignment-biases-into/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Trevor Cohn, Cong Duy Vu Hoang, Ekaterina Vymolova, et al.*2016 · 241 citations*
27. **[Attention-based Multimodal Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/huang-2016-attention-based-multimodal-neural-machine/) [Conference on Machine Translation: Shared Task Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-shared-task-papers/)**Po-Yao Huang, Frederick Liu, Sz-Rung Shiang, et al.*2016 · 236 citations*
28. **[Sparse Overcomplete Word Vector Representations](https://md.research.elamur.ai/free/en/papers/faruqui-2015-sparse-overcomplete-word-vector-representations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Manaal Faruqui, Yulia Tsvetkov, Dani Yogatama, et al.*2015 · 228 citations*
29. **[Evaluation of Word Vector Representations by Subspace Alignment ↗](https://aclanthology.org/D15-1243/) Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · no summary yet**Yulia Tsvetkov et al.*2015 · 209 citations*
30. **[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*
31. **[Compound Probabilistic Context-Free Grammars for Grammar Induction](https://md.research.elamur.ai/free/en/papers/kim-2019-compound-probabilistic-context-free-grammars/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yoon Kim, Chris Dyer, Alexander Rush*2019 · 201 citations*
32. **[Finding syntax in human encephalography with beam search ↗](https://aclanthology.org/P18-1254/) Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**John Hale et al.*2018 · 182 citations*
33. **[Morphological Inflection Generation Using Character Sequence to Sequence Learning ↗](https://aclanthology.org/N16-1077/) Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Manaal Faruqui et al.*2016 · 181 citations*
34. **[Unsupervised Recurrent Neural Network Grammars ↗](https://aclanthology.org/N19-1114/) Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · no summary yet**Yoon Kim et al.*2019 · 168 citations*
35. **[Not All Contexts Are Created Equal: Better Word Representations with Variable Attention ↗](https://aclanthology.org/D15-1161/) Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · no summary yet**Wang Ling et al.*2015 · 166 citations*
36. **[Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation](https://md.research.elamur.ai/free/en/papers/huang-2019-achieving-verified-robustness-symbol-substitutions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Po-Sen Huang, Robert Stanforth, Johannes Welbl, et al.*2019 · 163 citations*
37. **[Joshua: An Open Source Toolkit for Parsing-Based Machine Translation](https://md.research.elamur.ai/free/en/papers/li-2009-joshua-open-source-toolkit-parsing/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Zhifei Li, Chris Callison-Burch, Chris Dyer, et al.*2009 · 163 citations*
38. [**Unsupervised Text Style Transfer using Language Models as Discriminators arXiv:1805.11749**Zichao Yang, Zhiting Hu, Chris Dyer, et al.*2018 · 161 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-unsupervised-text-style-transfer-using/)
39. [**Frame-Semantic Parsing with Softmax-Margin Segmental RNNs and a Syntactic Scaffold arXiv:1706.09528**Swabha Swayamdipta, Sam Thomson, Chris Dyer, et al.*2017 · 160 citations*](https://md.research.elamur.ai/free/en/papers/swayamdipta-2017-frame-semantic-parsing-softmax-margin/)
40. **[Discriminative Lexical Semantic Segmentation with Gaps: Running the MWE Gamut](https://md.research.elamur.ai/free/en/papers/schneider-2014-discriminative-lexical-semantic-segmentation-gaps/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nathan Schneider, Emily Danchik, Chris Dyer, et al.*2014 · 159 citations*
41. **[A Gibbs Sampler for Phrasal Synchronous Grammar Induction ↗](https://aclanthology.org/P09-1088/) Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP · no summary yet**Phil Blunsom et al.*2009 · 153 citations*
42. [**Generation from Abstract Meaning Representation using Tree Transducers**Jeffrey Flanigan, Chris Dyer, Noah A. Smith, et al.*Machine translation · 152 citations*](https://md.research.elamur.ai/free/en/papers/flanigan-2016-generation-abstract-meaning-representation-tree/)
43. **[Syntactic Scaffolds for Semantic Structures ↗](https://aclanthology.org/D18-1412/) Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yet**Swabha Swayamdipta et al.*2018 · 142 citations*
44. **[Efficient Minimum Error Rate Training and Minimum Bayes-Risk Decoding for Translation Hypergraphs and Lattices ↗](https://aclanthology.org/P09-1019/) Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP · no summary yet**Shankar Kumar et al.*2009 · 134 citations*
45. **[Machine Learning for Ancient Languages: A Survey](https://md.research.elamur.ai/free/en/papers/sommerschield-2023-machine-learning-ancient-languages-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Thea Sommerschield, Yannis Assael, John Pavlopoulos, et al.*2023 · 124 citations*
46. **[Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings ↗](https://aclanthology.org/D16-1153/) Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · no summary yet**Akash Bharadwaj et al.*2016 · 123 citations*
47. **[Reference-Aware Language Models ↗](https://aclanthology.org/D17-1197/) Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · no summary yet**Zichao Yang et al.*2017 · 113 citations*
48. **[Learning Robust and Multilingual Speech Representations ↗](https://aclanthology.org/2020.findings-emnlp.106/) Findings of the Association for Computational Linguistics: EMNLP 2020 · no summary yet**Kazuya Kawakami et al.*2020 · 102 citations*
49. **[Training with Exploration Improves a Greedy Stack LSTM Parser ↗](https://aclanthology.org/D16-1211/) Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · no summary yet**Miguel Ballesteros et al.*2016 · 99 citations*
50. **[Semantic Parsing with Semi-Supervised Sequential Autoencoders ↗](https://aclanthology.org/D16-1116/) Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · no summary yet**Tomáš Kočiský et al.*2016 · 98 citations*
51. **[Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning ↗](https://aclanthology.org/P16-1013/) Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Yulia Tsvetkov et al.*2016 · 97 citations*
52. **[Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning ↗](https://aclanthology.org/N16-1161/) Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Yulia Tsvetkov et al.*2016 · 94 citations*
53. [**End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering arXiv:2106.05346**Devendra Singh Sachan, Siva Reddy, William Hamilton, et al.*2021 · 88 citations*](https://md.research.elamur.ai/free/en/papers/sachan-2021-end-end-training-multi-document/)
54. **[Frame-Semantic Role Labeling with Heterogeneous Annotations](https://md.research.elamur.ai/free/en/papers/kshirsagar-2015-frame-semantic-role-labeling-heterogeneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Meghana Kshirsagar, Sam Thomson, Nathan Schneider, et al.*2015 · 88 citations*
55. **[CMU at SemEval-2016 Task 8: Graph-based AMR Parsing with Infinite Ramp Loss ↗](https://aclanthology.org/S16-1186/) Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016) · no summary yet**Jeffrey Flanigan et al.*2016 · 85 citations*
56. [**What Do Recurrent Neural Network Grammars Learn About Syntax? arXiv:1611.05774**Adhiguna Kuncoro, Miguel Ballesteros, Lingpeng Kong, et al.*2016 · 83 citations*](https://md.research.elamur.ai/free/en/papers/kuncoro-2016-recurrent-neural-network-grammars-learn/)
57. **[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*
58. **[Better Document-Level Machine Translation with Bayes' Rule](https://md.research.elamur.ai/free/en/papers/yu-2020-better-document-level-machine-translation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Lei Yu, Laurent Sartran, Wojciech Stokowiec, et al.*2020 · 72 citations*
59. **[Paraphrasing 4 Microblog Normalization ↗](https://aclanthology.org/D13-1008/) Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing · no summary yet**Wang Ling et al.*2013 · 62 citations*
60. **[On-the-fly Operation Batching in Dynamic Computation Graphs ↗](https://arxiv.org/abs/1705.07860) arXiv (Cornell University) · no summary yet**Graham Neubig, Yoav Goldberg, Chris Dyer*2017 · 57 citations*
61. **[Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser ↗](https://aclanthology.org/D16-1180/) Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · no summary yet**Adhiguna Kuncoro et al.*2016 · 57 citations*
62. **[Augmenting English Adjective Senses with Supersenses](https://md.research.elamur.ai/free/en/papers/tsvetkov-2014-augmenting-english-adjective-senses-supersenses/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yulia Tsvetkov, Nathan Schneider, Dirk Hovy, et al.*2014 · 57 citations*
63. **[A Bayesian Model for Learning SCFGs with Discontiguous Rules ↗](https://aclanthology.org/D12-1021/) Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning · no summary yet**Abby Levenberg, Chris Dyer, Phil Blunsom*2012 · 39 citations*
64. [**Ontology-Aware Token Embeddings for Prepositional Phrase Attachment**Pradeep Dasigi, Waleed Ammar, Chris Dyer, et al.*English · 35 citations*](https://md.research.elamur.ai/free/en/papers/dasigi-2017-ontology-aware-token-embeddings-prepositional/)
65. **[Generalizing and Hybridizing Count-based and Neural Language Models ↗](https://aclanthology.org/D16-1124/) Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · no summary yet**Graham Neubig, Chris Dyer*2016 · 34 citations*
66. **[Using Morphological Knowledge in Open-Vocabulary Neural Language Models ↗](https://aclanthology.org/N18-1130/) Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) · no summary yet**Austin Matthews, Graham Neubig, Chris Dyer*2018 · 28 citations*
67. **[Unifying Bayesian Inference and Vector Space Models for Improved Decipherment ↗](https://aclanthology.org/P15-1081/) 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) · no summary yet**Qing Dou et al.*2015 · 28 citations*
68. **[Joshua 2.0: A Toolkit for Parsing-Based Machine Translation with Syntax, Semirings, Discriminative Training and Other Goodies ↗](https://aclanthology.org/W10-1718/) Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR · no summary yet**Zhifei Li et al.*2010 · 26 citations*
69. **[The CMU Machine Translation Systems at WMT 2013: Syntax, Synthetic Translation Options, and Pseudo-References ↗](https://aclanthology.org/W13-2205/) Proceedings of the Eighth Workshop on Statistical Machine Translation · no summary yet**Waleed Ammar et al.*2013 · 22 citations*
70. **[A Continuous Relaxation of Beam Search for End-to-End Training of Neural Sequence Models ↗](https://doi.org/10.1609/aaai.v32i1.11806) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Kartik Goyal et al.*2018 · 18 citations*
71. **[Supersense Tagging for Arabic: the MT-in-the-Middle Attack](https://md.research.elamur.ai/free/en/papers/schneider-2013-supersense-tagging-arabic-mt-middle/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nathan Schneider, Behrang Mohit, Chris Dyer, et al.*2013 · 10 citations*
72. **[From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17,042) ↗](https://doi.org/10.4230/dagrep.7.1.129) DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · no summary yet**Phil Blunsom et al.*2017 · 7 citations*
73. **[Comparing Top-Down and Bottom-Up Neural Generative Dependency Models ↗](https://aclanthology.org/K19-1022/) Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL) · no summary yet**Austin Matthews, Graham Neubig, Chris Dyer*2019 · 3 citations*
74. **[Practical Neural Networks for NLP: From Theory to Code ↗](https://openalex.org/W3088771895) Empirical Methods in Natural Language Processing · no summary yet**Chris Dyer, Yoav Goldberg, Graham Neubig*2016 · 2 citations*
75. **[Paraphrase-Supervised Models of Compositionality ↗](https://arxiv.org/abs/1801.10293) arXiv:1801.10293 · no summary yet**Avneesh Saluja, Chris Dyer, Jean-David Ruvini*2018 · 1 citation*
76. **[Enabling arbitrary translation objectives with Adaptive Tree Search ↗](https://arxiv.org/abs/2202.11444) arXiv:2202.11444 · no summary yet**Wang Ling et al.*2022*