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Who cites «Effective Approaches to Attention-based Neural Machine Translation»

1,474 papers of our library cite it (of the 140,884 whose bibliographies we read) · 129 with a page here, the most cited first · page 2 of 2 · 101–129 · ← the paper

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  1. AudioCaps: Generating Captions for Audios in The WildChris Dongjoo Kim, Byeongchang Kim, Hyunmin Lee, et al.2019 · 176 citations
  2. Effective Domain Mixing for Neural Machine TranslationDenny Britz, Quoc Le, Reid Pryzant2017 · 155 citations
  3. Neural Net Models of Open-domain Discourse CoherenceJiwei Li, Dan Jurafsky2017 · 147 citations
  4. SGM: Sequence Generation Model for Multi-label ClassificationPengcheng Yang, Xu Sun, Wei Li, et al.2018 · 145 citations
  5. Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning RepresentationsRik van Noord, Johan Bos2017 · 137 citations
  6. Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image DescriptionDesmond Elliott, Stella Frank, Loïc Barrault, et al.2017 · 133 citations
  7. Scheduled Multi-Task Learning: From Syntax to TranslationEliyahu Kiperwasser, Miguel Ballesteros2018 · 130 citations
  8. Does Syntax Need to Grow on Trees? Sources of Hierarchical Inductive Bias in Sequence-to-Sequence NetworksR. Thomas McCoy, Robert Frank, Tal Linzen2020 · 122 citations
  9. Simple and Effective Text Simplification Using Semantic and Neural MethodsElior Sulem, Omri Abend, Ari Rappoport2018 · 113 citations
  10. Learning to Reason Deductively: Math Word Problem Solving as Complex Relation ExtractionZhanming Jie, Jierui Li, Wei Lu2022 · 102 citations
  11. BlonDe: An Automatic Evaluation Metric for Document-level Machine TranslationYuchen Jiang, Tianyu Liu, Shuming Ma, et al.2022 · 85 citations
  12. Finding the Optimal Vocabulary Size for Neural Machine TranslationThamme Gowda, Jonathan May2020 · 72 citations
  13. MIDAS: A Dialog Act Annotation Scheme for Open Domain Human-Machine Spoken ConversationsDian Yu, Zhou Yu2021 · 47 citations
  14. Exploring Author Context for Detecting Intended vs Perceived SarcasmSilviu Oprea, Walid Magdy2019 · 47 citations
  15. Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological TaggingNasser Zalmout, Nizar Habash2020 · 44 citations
  16. Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation ClassificationWei Shi, Vera Demberg2019 · 36 citations
  17. Factorising AMR generation through syntaxKris Cao, Stephen Clark2019 · 28 citations
  18. Morphological Word Embeddings for Arabic Neural Machine Translation in Low-Resource SettingsPamela Shapiro, Kevin Duh2018 · 25 citations
  19. The Role of Pragmatic and Discourse Context in Determining Argument ImpactEsin Durmus, Faisal Ladhak, Claire Cardie2019 · 24 citations
  20. A Pointer Network Architecture for Joint Morphological Segmentation and TaggingAmit Seker, Reut Tsarfaty2020 · 21 citations
  21. A Distributional and Orthographic Aggregation Model for English Derivational MorphologyDaniel Deutsch, John Hewitt, Dan Roth2018 · 19 citations
  22. Wiktionary Normalization of Translations and Morphological InformationWinston Wu, David Yarowsky2020 · 12 citations
  23. Amharic-Arabic Neural Machine TranslationIbrahim Gashaw, H L Shashirekha2019 · 11 citations
  24. Constrained Sequence-to-sequence Semitic Root Extraction for Enriching Word EmbeddingsAhmed El-Kishky, Xingyu Fu, Aseel Addawood, et al.2019 · 6 citations
  25. Domain Adaptation for Arabic Machine Translation: The Case of Financial TextsEmad A. Alghamdi, Jezia Zakraoui, Fares A. Abanmy2023 · 3 citations
  26. Automated Prediction of Medieval Arabic DiacriticsKhalid Alnajjar, Mika Hamalainen, Niko Partanen, et al.2020 · 3 citations
  27. Mimicking Neural Machine Translation History for Pedagogic ReasonsVincent Vandeghinste2026
  28. Survey on Document-level Neural Machine Translation (文档级神经机器翻译综述)Xinglin Lv (吕星林), Junhui Li (李军辉), Shimin Tao (陶仕敏), et al.2024
  29. The Truth, The Whole Truth, and Nothing but the Truth: A New Benchmark Dataset for Hebrew Text Credibility AssessmentBen Hagag, Reut Tsarfaty2023

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