Who Cited It

Recurrent Convolutional Neural Networks for Text Classification

2015 · Proceedings of the AAAI Conference on Artificial Intelligence · 2,314 citations · 2 from inside this corpus

Siwei Lai, Liheng Xu, Kang Liu, Jun Zhao

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.

Recurrent Convolutional Neural Networks for Text Classification (2015)Recurrent Convolutional Neura…Reducing the Dimensionality of Data with Neural Networks (2006)Reducing the Dimensionality o…Distributed Representations of Words and Phrases and their Compositionality (2013)Distributed Representations o…Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank (2013)Recursive Deep Models for Sem…Natural Language Processing (almost) from Scratch (2011)Natural Language Processing (…Distributed Representations of Sentences and Documents (2014)Distributed Representations o…Natural Language Processing (almost) from Scratch (2011)Natural Language Processing (…Linguistic Regularities in Continuous Space Word Representations (2013)Linguistic Regularities in Co…A neural probabilistic language model (2003)A neural probabilistic langua…Why Does Unsupervised Pre-training Help Deep Learning? (2010)Why Does Unsupervised Pre-tra…Word Representations: A Simple and General Method for Semi-Supervised Learning (2010)Word Representations: A Simpl…Feature selection, L 1 vs. L 2 regularization, and rotational invariance (2004)Feature selection, L 1 vs. L …Don't count, predict! A systematic comparison of context-counting vs. context-predicting … (2014)Don't count, predict! A syste…Hierarchical Attention Networks for Document Classification (2016)Hierarchical Attention Networ…TabNet: Attentive Interpretable Tabular Learning (2021)TabNet: Attentive Interpretab…
14 of 14 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.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
Reducing the Dimensionality of Data with Neural Networks200621,247
Distributed Representations of Words and Phrases and their Compositionality201318,054
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank20136,849
Natural Language Processing (almost) from Scratch20115,174
Distributed Representations of Sentences and Documents20145,121
Natural Language Processing (almost) from Scratch20113,991
Linguistic Regularities in Continuous Space Word Representations20132,885
A neural probabilistic language model20032,675
Why Does Unsupervised Pre-training Help Deep Learning?20102,114
Word Representations: A Simple and General Method for Semi-Supervised Learning20101,941
Feature selection, L 1 vs. L 2 regularization, and rotational invariance20041,603
Don't count, predict! A systematic comparison of context-counting vs. context-predicting …20141,388

What cites it, inside the corpus

PaperYearCited
Hierarchical Attention Networks for Document Classification20164,871
TabNet: Attentive Interpretable Tabular Learning20211,700

Links

DOI · Open access copy · OpenAlex record

Topics

Topic ModelingComputer Science
Text and Document Classification TechnologiesComputer Science
Advanced Text Analysis TechniquesComputer Science

Is this record sound?

complete

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

  • supports4 author record(s) attached.
  • supports52 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 2026-09-04T03:58:50+00:00.

sha256 86a6d6715ff540a0…