Who Cited It

Teaching Machines to Read and Comprehend

2015 · Oxford University Research Archive (ORA) (University of Oxford) · 1,939 citations · 10 from inside this corpus

Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom

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.

Teaching Machines to Read and Comprehend (2015)Teaching Machines to Read and…Long Short-Term Memory (1997)Long Short-Term MemorySequence to Sequence Learning with Neural Networks (2014)Sequence to Sequence Learning…Understanding natural language (1972)Understanding natural languageHierarchical Attention Networks for Document Classification (2016)Hierarchical Attention Networ…Get To The Point: Summarization with Pointer-Generator Networks (2017)Get To The Point: Summarizati…Deep learning for healthcare: review, opportunities and challenges (2017)Deep learning for healthcare:…fairseq: A Fast, Extensible Toolkit for Sequence Modeling (2019)fairseq: A Fast, Extensible T…Attention-based LSTM for Aspect-level Sentiment Classification (2016)Attention-based LSTM for Aspe…Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond (2016)Abstractive Text Summarizatio…Know What You Don’t Know: Unanswerable Questions for SQuAD (2018)Know What You Don’t Know: Una…Natural Questions: A Benchmark for Question Answering Research (2019)Natural Questions: A Benchmar…Text Summarization with Pretrained Encoders (2019)Text Summarization with Pretr…Reading Wikipedia to Answer Open-Domain Questions (2017)Reading Wikipedia to Answer O…
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.
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
Long Short-Term Memory1997101,359
Sequence to Sequence Learning with Neural Networks20143,514
Understanding natural language19722,846

What cites it, inside the corpus

PaperYearCited
Hierarchical Attention Networks for Document Classification20164,871
Get To The Point: Summarization with Pointer-Generator Networks20173,935
Deep learning for healthcare: review, opportunities and challenges20173,115
fairseq: A Fast, Extensible Toolkit for Sequence Modeling20192,511
Attention-based LSTM for Aspect-level Sentiment Classification20162,380
Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond20162,233
Know What You Don’t Know: Unanswerable Questions for SQuAD20182,196
Natural Questions: A Benchmark for Question Answering Research20192,095
Text Summarization with Pretrained Encoders20191,633
Reading Wikipedia to Answer Open-Domain Questions20171,454

Links

Open access copy · OpenAlex record

Topics

Topic ModelingComputer Science
Natural Language Processing TechniquesComputer Science
Advanced Text Analysis TechniquesComputer Science

Is this record sound?

complete

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

  • supports7 author record(s) attached.
  • supports16 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…