---
title: "Who cites Effective Approaches to Attention-based Neural…"
description: "1,474 papers of the Elamur Research library cite «Effective Approaches to Attention-based Neural Machine Translation», found in their bibliographies ·…"
canonical: "https://research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/cited-by/page/2/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/cited-by/page/2/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Effective Approaches to Attention-based Neural…](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/) / [cited by](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/cited-by/) / page 2

# 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](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/)

[← prev](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/cited-by/) **2**

101. [**AudioCaps: Generating Captions for Audios in The Wild**Chris Dongjoo Kim, Byeongchang Kim, Hyunmin Lee, et al.*2019 · 176 citations*](https://md.research.elamur.ai/free/en/papers/kim-2019-audiocaps-generating-captions-audios-wild/)
102. [**Effective Domain Mixing for Neural Machine Translation**Denny Britz, Quoc Le, Reid Pryzant*2017 · 155 citations*](https://md.research.elamur.ai/free/en/papers/britz-2017-effective-domain-mixing-neural-machine/)
103. [**Neural Net Models of Open-domain Discourse Coherence**Jiwei Li, Dan Jurafsky*2017 · 147 citations*](https://md.research.elamur.ai/free/en/papers/li-2017-neural-net-models-open-domain/)
104. [**SGM: Sequence Generation Model for Multi-label Classification**Pengcheng Yang, Xu Sun, Wei Li, et al.*2018 · 145 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-sgm-sequence-generation-model-multi/)
105. [**Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representations**Rik van Noord, Johan Bos*2017 · 137 citations*](https://md.research.elamur.ai/free/en/papers/noord-2017-neural-semantic-parsing-character-based/)
106. [**Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description**Desmond Elliott, Stella Frank, Loïc Barrault, et al.*2017 · 133 citations*](https://md.research.elamur.ai/free/en/papers/elliott-2017-findings-second-shared-task-multimodal/)
107. [**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/)
108. [**Does Syntax Need to Grow on Trees? Sources of Hierarchical Inductive Bias in Sequence-to-Sequence Networks**R. Thomas McCoy, Robert Frank, Tal Linzen*2020 · 122 citations*](https://md.research.elamur.ai/free/en/papers/mccoy-2020-does-syntax-need-grow-trees/)
109. [**Simple and Effective Text Simplification Using Semantic and Neural Methods**Elior Sulem, Omri Abend, Ari Rappoport*2018 · 113 citations*](https://md.research.elamur.ai/free/en/papers/sulem-2018-simple-effective-text-simplification-semantic/)
110. [**Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction**Zhanming Jie, Jierui Li, Wei Lu*2022 · 102 citations*](https://md.research.elamur.ai/free/en/papers/jie-2022-learning-reason-deductively-math-word/)
111. [**BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation**Yuchen Jiang, Tianyu Liu, Shuming Ma, et al.*2022 · 85 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-blonde-automatic-evaluation-metric-document/)
112. [**Finding the Optimal Vocabulary Size for Neural Machine Translation**Thamme Gowda, Jonathan May*2020 · 72 citations*](https://md.research.elamur.ai/free/en/papers/gowda-2020-finding-optimal-vocabulary-size-neural/)
113. [**MIDAS: A Dialog Act Annotation Scheme for Open Domain Human-Machine Spoken Conversations**Dian Yu, Zhou Yu*2021 · 47 citations*](https://md.research.elamur.ai/free/en/papers/yu-2021-midas-dialog-act-annotation-scheme/)
114. [**Exploring Author Context for Detecting Intended vs Perceived Sarcasm**Silviu Oprea, Walid Magdy*2019 · 47 citations*](https://md.research.elamur.ai/free/en/papers/oprea-2019-exploring-author-context-detecting-intended/)
115. [**Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging**Nasser Zalmout, Nizar Habash*2020 · 44 citations*](https://md.research.elamur.ai/free/en/papers/zalmout-2020-joint-diacritization-lemmatization-normalization-fine/)
116. [**Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification**Wei Shi, Vera Demberg*2019 · 36 citations*](https://md.research.elamur.ai/free/en/papers/shi-2019-learning-explicitate-connectives-seq2seq-network/)
117. [**Factorising AMR generation through syntax**Kris Cao, Stephen Clark*2019 · 28 citations*](https://md.research.elamur.ai/free/en/papers/cao-2019-factorising-amr-generation-through-syntax/)
118. [**Morphological Word Embeddings for Arabic Neural Machine Translation in Low-Resource Settings**Pamela Shapiro, Kevin Duh*2018 · 25 citations*](https://md.research.elamur.ai/free/en/papers/shapiro-2018-morphological-word-embeddings-arabic-neural/)
119. [**The Role of Pragmatic and Discourse Context in Determining Argument Impact**Esin Durmus, Faisal Ladhak, Claire Cardie*2019 · 24 citations*](https://md.research.elamur.ai/free/en/papers/durmus-2019-role-pragmatic-discourse-context-determining/)
120. [**A Pointer Network Architecture for Joint Morphological Segmentation and Tagging**Amit Seker, Reut Tsarfaty*2020 · 21 citations*](https://md.research.elamur.ai/free/en/papers/seker-2020-pointer-network-architecture-joint-morphological/)
121. [**A Distributional and Orthographic Aggregation Model for English Derivational Morphology**Daniel Deutsch, John Hewitt, Dan Roth*2018 · 19 citations*](https://md.research.elamur.ai/free/en/papers/deutsch-2018-distributional-orthographic-aggregation-model-english/)
122. [**Wiktionary Normalization of Translations and Morphological Information**Winston Wu, David Yarowsky*2020 · 12 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-wiktionary-normalization/)
123. [**Amharic-Arabic Neural Machine Translation**Ibrahim Gashaw, H L Shashirekha*2019 · 11 citations*](https://md.research.elamur.ai/free/en/papers/gashaw-2019-amharic-arabic-neural-machine-translation/)
124. [**Constrained Sequence-to-sequence Semitic Root Extraction for Enriching Word Embeddings**Ahmed El-Kishky, Xingyu Fu, Aseel Addawood, et al.*2019 · 6 citations*](https://md.research.elamur.ai/free/en/papers/kishky-2019-constrained-sequence-sequence-semitic-root/)
125. [**Domain Adaptation for Arabic Machine Translation: The Case of Financial Texts**Emad A. Alghamdi, Jezia Zakraoui, Fares A. Abanmy*2023 · 3 citations*](https://md.research.elamur.ai/free/en/papers/alghamdi-2023-domain-adaptation-arabic-machine-translation/)
126. [**Automated Prediction of Medieval Arabic Diacritics**Khalid Alnajjar, Mika Hamalainen, Niko Partanen, et al.*2020 · 3 citations*](https://md.research.elamur.ai/free/en/papers/alnajjar-2020-automated-prediction-medieval-arabic-diacritics/)
127. [**Mimicking Neural Machine Translation History for Pedagogic Reasons**Vincent Vandeghinste*2026*](https://md.research.elamur.ai/free/en/papers/vandeghinste-2026-mimicking-neural-machine-translation-history/)
128. [**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*](https://md.research.elamur.ai/free/en/papers/lv-2024-document-level-neural/)
129. [**The Truth, The Whole Truth, and Nothing but the Truth: A New Benchmark Dataset for Hebrew Text Credibility Assessment**Ben Hagag, Reut Tsarfaty*2023*](https://md.research.elamur.ai/free/en/papers/hagag-2023-truth-whole-truth-nothing-but/)

[← prev](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/cited-by/) **2**

1,345 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/) — Effective Approaches to Attention-based Neural Machine Translation