Paper Citation Record · LEDGER

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification

As of 16 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:1908.06263.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.06263 v3

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:54:55.021553Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

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verified fuzzy22
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f3ef649b-effd-429e-8be3-75cc6fb6ef5c · outbound

This paper cites Convolutional Neural Networks for Sentence Classification.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Convolutional Neural Networks for Sentence Classification

Reference 1

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Observation e0dd9668-8260-421f-9b42-96b610338bdb · outbound

This paper cites Se mantic clustering and convolutional neural network for short text ca tegorization.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Se mantic clustering and convolutional neural network for short text ca tegorization

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.320645Z

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Observation c9d1403a-4649-462b-94a6-7d4f14ad28fd · outbound

This paper cites Attention pooling - based convolutional neural network for sentence modelling.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Attention pooling - based convolutional neural network for sentence modelling

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.310494Z

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Observation 7b9ff3e2-89ab-4cc8-b824-8dc4e983298b · outbound

This paper cites An Attention-Gated Convolutional Neural Network for Sentence Classification.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification An Attention-Gated Convolutional Neural Network for Sentence Classification

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-14T12:54:55.103493Z

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Observation 00e105fb-717c-43f1-83de-adae9c930223 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Efficient Estimation of Word Representations in Vector Space

Reference 5

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Observation 43f8bbe5-7009-4eb0-b78f-5f6ddde3f3c8 · outbound

This paper cites Distributed representations of words and phrases and their compositionality.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Distributed representations of words and phrases and their compositionality

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.301212Z

Source-reported events for the cited work

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Observation f10eb869-5d87-4d60-ad9f-a4134ce650a1 · outbound

This paper cites A com parison of event models for naive bayes text classification.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification A com parison of event models for naive bayes text classification

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.291924Z

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Observation e15080da-f85a-4f4d-a788-57e4cac153e7 · outbound

This paper cites Text classifica tion using mach ine learning technique s.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Text classifica tion using mach ine learning technique s

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.282578Z

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Observation 8d3a4072-9088-46a7-b1a8-b998678fc7bb · outbound

This paper cites Text categorization based on LDA and SVM.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Text categorization based on LDA and SVM

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.273799Z

Source-reported events for the cited work

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Observation 7275c83e-9527-4f7f-b088-43c13db3e1b5 · outbound

This paper cites A s enti mental education: S e ntiment analysis using sub jectivity summarization based on minimum cuts.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification A s enti mental education: S e ntiment analysis using sub jectivity summarization based on minimum cuts

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.265166Z

Source-reported events for the cited work

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Observation 3752b8a2-d98c-473f-ab4f-c074d585ed67 · outbound

This paper cites Mining and summar izing customer revi ews.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Mining and summar izing customer revi ews

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.256248Z

Source-reported events for the cited work

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Observation eb5488b5-4c40-4f41-b78e-945dba66a34b · outbound

This paper cites Practical recommendations for gradient - based training of deep architectures.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Practical recommendations for gradient - based training of deep architectures

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.247208Z

Source-reported events for the cited work

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Observation effd726e-ef3e-4b56-b656-96ef3d1c0484 · outbound

This paper cites Towards automatically - tuned neural networks.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Towards automatically - tuned neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.238432Z

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Observation d86bff81-ac43-4760-9620-083db3588411 · outbound

This paper cites Bayesian Optimization of Text Representations.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Bayesian Optimization of Text Representations

Reference 14

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Observation 90b4e581-9d35-4d08-b619-97f5fc8f0841 · outbound

This paper cites Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.229628Z

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Observation 89d67359-b8e3-476d-bb96-339739273acc · outbound

This paper cites Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search

Reference 16

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Observation 3feb9fbc-3d72-48df-afbd-2df3f8c5540c · outbound

This paper cites An anal y s is of single - layer network s in unsupervised feature learning.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification An anal y s is of single - layer network s in unsupervised feature learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.220227Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9d8abe93-3f5e-4da2-a7bc-1b0f6ce63829 · outbound

This paper cites The effects of hyperparameters on SGD training of neur al networks.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification The effects of hyperparameters on SGD training of neur al networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.211169Z

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Observation ae5b6ecb-0350-4b22-bb20-76a3e9c468c1 · outbound

This paper cites Attention is all you need.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Attention is all you need

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.201859Z

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Observation 6966434b-b4ad-469b-9c41-66b0e72a2842 · outbound

This paper cites ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs

Reference 21

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Observation 84f75759-e4fd-480d-9d42-6c5d230eaba2 · outbound

This paper cites Dropout: a simple way to prevent neur al networks fro m ov erfitting.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Dropout: a simple way to prevent neur al networks fro m ov erfitting

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.192013Z

Source-reported events for the cited work

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Observation 2ccd3bb3-f92f-40cc-a577-03e794cb5ba0 · outbound

This paper cites Self - normalizing neural networks.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Self - normalizing neural networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.182756Z

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Observation 7f275dd8-05ef-4374-9d46-ea0ea258ee75 · outbound

This paper cites Learning question cla ssifiers.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Learning question cla ssifiers

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.172656Z

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Observation 44ea6c36-6e7f-454d-ba5f-5cee25c75e95 · outbound

This paper cites Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.162584Z

Source-reported events for the cited work

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Observation 6a5b1c52-8921-4871-ad5e-36167cf5cd32 · outbound

This paper cites Recursive deep models for semantic compositionality over a sen timent treebank.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Recursive deep models for semantic compositionality over a sen timent treebank

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.151920Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 90fe4516-d748-47dc-8cb0-71a2187836b3 · outbound

This paper cites Rectified linear units improve restricted boltzmann machines.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Rectified linear units improve restricted boltzmann machines

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.142132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2a9ebbc9-f3bf-4e94-b01a-fc62f89aae66 · outbound

This paper cites Rec t i fier nonlinearities improv e neural network acoustic models.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Rec t i fier nonlinearities improv e neural network acoustic models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.132149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 96b8bfe4-5969-490e-a99c-d4c7fe2d0976 · outbound

This paper cites Delving deep into rectifiers: Surpassing human - level performance on imagenet classification.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Delving deep into rectifiers: Surpassing human - level performance on imagenet classification

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:54:55.122087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 84bd6493-359a-4f7e-99df-546459b11f1b · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-14T12:54:55.021553Z

Source-reported events for the cited work

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