Who Cited It

An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

2018 · arXiv (Cornell University) · 4,364 citations · 1 from inside this corpus

Shaojie Bai, J. Zico Kolter, Vladlen Koltun

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.

An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode… (2018)An Empirical Evaluation of Ge…[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics… (2015)[No title in the source recor…Dropout: a simple way to prevent neural networks from overfitting (2014)Dropout: a simple way to prev…Bidirectional recurrent neural networks (1997)Bidirectional recurrent neura…Building a Large Annotated Corpus of English: The Penn Treebank (1993)Building a Large Annotated Co…A unified architecture for natural language processing (2008)A unified architecture for na…Natural Language Processing (almost) from Scratch (2011)Natural Language Processing (…Backpropagation through time: what it does and how to do it (1990)Backpropagation through time:…Sequence to Sequence Learning with Neural Networks (2014)Sequence to Sequence Learning…Phoneme recognition using time-delay neural networks (1989)Phoneme recognition using tim…Parallel Networks that Learn to Pronounce English Text (1987)Parallel Networks that Learn …Connectionist learning procedures (1989)Connectionist learning proced…An Empirical Exploration of Recurrent Network Architectures (2015)An Empirical Exploration of R…Transformer-XL: Attentive Language Models beyond a Fixed-Length Context (2019)Transformer-XL: Attentive Lan…
13 of 13 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
[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…201550,396
Dropout: a simple way to prevent neural networks from overfitting201434,236
Bidirectional recurrent neural networks199710,294
Building a Large Annotated Corpus of English: The Penn Treebank19937,538
A unified architecture for natural language processing20085,207
Natural Language Processing (almost) from Scratch20115,174
Backpropagation through time: what it does and how to do it19904,971
Sequence to Sequence Learning with Neural Networks20143,514
Phoneme recognition using time-delay neural networks19892,650
Parallel Networks that Learn to Pronounce English Text19871,557
Connectionist learning procedures19891,466
An Empirical Exploration of Recurrent Network Architectures20151,406

What cites it, inside the corpus

PaperYearCited
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context20193,202

Links

DOI · Open access copy · OpenAlex record

Topics

Topic ModelingComputer Science
Natural Language Processing TechniquesComputer Science
Music and Audio ProcessingComputer Science

Is this record sound?

complete

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

  • supports3 author record(s) attached.
  • supports66 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 2026-09-04T03:58:44+00:00.

sha256 648f8491aaceaa34…