Who Cited It

Convolutional Sequence to Sequence Learning

2017 · arXiv (Cornell University) · 1,903 citations · 6 from inside this corpus

Jonas Gehring low, Michael Auli, David Grangier, Denis Yarats low, Yann Dauphin

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Convolutional Sequence to Sequence Learning (2017)Convolutional Sequence to Seq…Long Short-Term Memory (1997)Long Short-Term MemoryBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh… (2024)Batch Normalization: Accelera…ROUGE: A Package for Automatic Evaluation of Summaries (2004)ROUGE: A Package for Automati…Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Tr… (2016)Google's Neural Machine Trans…The Handbook of brain theory and neural networks (1996)The Handbook of brain theory …On the importance of initialization and momentum in deep learning (2013)On the importance of initiali…Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Transla… (2014)Learning Phrase Representatio…Sequence to Sequence Learning with Neural Networks (2014)Sequence to Sequence Learning…Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond (2016)Abstractive Text Summarizatio…Attention Is All You Need (2025)Attention Is All You NeedRecent Trends in Deep Learning Based Natural Language Processing [Review Article] (2018)Recent Trends in Deep Learnin…fairseq: A Fast, Extensible Toolkit for Sequence Modeling (2019)fairseq: A Fast, Extensible T…GCNet: Non-Local Networks Meet Squeeze-Excitation Networks and Beyond (2019)GCNet: Non-Local Networks Mee…TabNet: Attentive Interpretable Tabular Learning (2021)TabNet: Attentive Interpretab…Pre-trained models for natural language processing: A survey (2020)Pre-trained models for natura…
15 of 15 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Long Short-Term Memory1997101,359
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…202415,663
ROUGE: A Package for Automatic Evaluation of Summaries20048,302
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Tr…20165,668
The Handbook of brain theory and neural networks19963,915
On the importance of initialization and momentum in deep learning20133,523
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Transla…20143,518
Sequence to Sequence Learning with Neural Networks20143,514
Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond20162,233

What cites it, inside the corpus

PaperYearCited
Attention Is All You Need20257,133
Recent Trends in Deep Learning Based Natural Language Processing [Review Article]20182,907
fairseq: A Fast, Extensible Toolkit for Sequence Modeling20192,511
GCNet: Non-Local Networks Meet Squeeze-Excitation Networks and Beyond20192,125
TabNet: Attentive Interpretable Tabular Learning20211,700
Pre-trained models for natural language processing: A survey20201,521

Links

DOI · Open access copy · OpenAlex record

Topics

Topic ModelingComputer Science
Natural Language Processing TechniquesComputer Science
Algorithms and Data CompressionComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports5 author record(s) attached.
  • supports37 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:52+00:00.

sha256 930f5bc64fea8a60…