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Visually Grounded Models of Spoken Language: A Survey of Datasets, Architectures and Evaluation Techniques
Visually Grounded Models of Spoken Language: A Survey of Datasets, Architectures and Evaluation Techniques
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Visually Grounded Models of Spoken Language: A Survey of Datasets, Architectures and Evaluation Techniques

The Journal of artificial intelligence research, 2022-01, Vol.73, p.673-707 [Peer Reviewed Journal]

2022. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.1.12967

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2
Representation of Linguistic Form and Function in Recurrent Neural Networks
Representation of Linguistic Form and Function in Recurrent Neural Networks
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Representation of Linguistic Form and Function in Recurrent Neural Networks

Computational linguistics - Association for Computational Linguistics, 2017-12, Vol.43 (4), p.761-780 [Peer Reviewed Journal]

Copyright MIT Press Journals, The Dec 2017 ;ISSN: 0891-2017 ;ISSN: 1530-9312 ;EISSN: 1530-9312 ;DOI: 10.1162/COLI_a_00300

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3
Analyzing and interpreting neural networks for NLP: A report on the first BlackboxNLP workshop
Analyzing and interpreting neural networks for NLP: A report on the first BlackboxNLP workshop
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Analyzing and interpreting neural networks for NLP: A report on the first BlackboxNLP workshop

Natural language engineering, 2019-07, Vol.25 (4), p.543-557 [Peer Reviewed Journal]

Cambridge University Press 2019 ;ISSN: 1351-3249 ;EISSN: 1469-8110 ;DOI: 10.1017/S135132491900024X

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4
Learning English with Peppa Pig
Learning English with Peppa Pig
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Learning English with Peppa Pig

Transactions of the Association for Computational Linguistics, 2022, Vol.10, p.922-936 [Peer Reviewed Journal]

2022. This work is published under https://creativecommons.org/licenses/by/4.0/legalcode (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Attribution ;ISSN: 2307-387X ;EISSN: 2307-387X ;DOI: 10.1162/tacl_a_00498

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5
A Survey on Multi-document Summarization and Domain-Oriented Approaches
A Survey on Multi-document Summarization and Domain-Oriented Approaches
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A Survey on Multi-document Summarization and Domain-Oriented Approaches

Journal of Information Systems and Telecommunication (JIST), 2022-12, Vol.10 (37), p.68-78 [Peer Reviewed Journal]

ISSN: 2322-1437 ;EISSN: 2322-1437 ;DOI: 10.52547/jist.16245.10.37.68

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6
Application of the Naive Bayes Classifier for Representation and Use of Heterogeneous and Incomplete Knowledge in Social Robotics
Application of the Naive Bayes Classifier for Representation and Use of Heterogeneous and Incomplete Knowledge in Social Robotics
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Application of the Naive Bayes Classifier for Representation and Use of Heterogeneous and Incomplete Knowledge in Social Robotics

Robotics (Basel), 2016-03, Vol.5 (1), p.6 [Peer Reviewed Journal]

ISSN: 2218-6581 ;EISSN: 2218-6581 ;DOI: 10.3390/robotics5010006

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7
Putting Natural in Natural Language Processing
Putting Natural in Natural Language Processing
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Putting Natural in Natural Language Processing

arXiv.org, 2023-05

2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2305.04572

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8
Visually grounded models of spoken language: A survey of datasets, architectures and evaluation techniques
Visually grounded models of spoken language: A survey of datasets, architectures and evaluation techniques
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Visually grounded models of spoken language: A survey of datasets, architectures and evaluation techniques

arXiv.org, 2021-10

2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2104.13225

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9
Symbolic inductive bias for visually grounded learning of spoken language
Symbolic inductive bias for visually grounded learning of spoken language
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Symbolic inductive bias for visually grounded learning of spoken language

arXiv.org, 2019-06

2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.1812.09244

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10
Encoding of lexical tone in self-supervised models of spoken language
Encoding of lexical tone in self-supervised models of spoken language
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Encoding of lexical tone in self-supervised models of spoken language

arXiv.org, 2024-04

2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2403.16865

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11
Correlating neural and symbolic representations of language
Correlating neural and symbolic representations of language
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Correlating neural and symbolic representations of language

arXiv.org, 2019-06

2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.1905.06401

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12
Quantifying the Plausibility of Context Reliance in Neural Machine Translation
Quantifying the Plausibility of Context Reliance in Neural Machine Translation
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Quantifying the Plausibility of Context Reliance in Neural Machine Translation

arXiv.org, 2024-03

2024. This work is published under http://creativecommons.org/licenses/by-sa/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by-sa/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2310.01188

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13
Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers
Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers
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Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers

arXiv.org, 2023-10

2023. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2310.09925

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14
Wave to Syntax: Probing spoken language models for syntax
Wave to Syntax: Probing spoken language models for syntax
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Wave to Syntax: Probing spoken language models for syntax

arXiv.org, 2023-05

2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2305.18957

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15
Learning to Understand Child-directed and Adult-directed Speech
Learning to Understand Child-directed and Adult-directed Speech
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Learning to Understand Child-directed and Adult-directed Speech

arXiv.org, 2021-07

2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2005.02721

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16
Quantifying Context Mixing in Transformers
Quantifying Context Mixing in Transformers
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Quantifying Context Mixing in Transformers

arXiv.org, 2023-02

2023. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2301.12971

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17
Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling
Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling
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Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling

arXiv.org, 2021-01

2021. This work is published under http://creativecommons.org/licenses/by-nc-sa/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by-nc-sa/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2101.11310

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18
Textual Supervision for Visually Grounded Spoken Language Understanding
Textual Supervision for Visually Grounded Spoken Language Understanding
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Textual Supervision for Visually Grounded Spoken Language Understanding

arXiv.org, 2020-10

2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2010.02806

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19
Learning English with Peppa Pig
Learning English with Peppa Pig
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Article 		Add to My Research

Learning English with Peppa Pig

arXiv.org, 2022-05

2022. This work is published under http://creativecommons.org/licenses/by-sa/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by-sa/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2202.12917

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20
Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations
Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations
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Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations

arXiv.org, 2022-01

2022. This work is published under http://creativecommons.org/licenses/by-sa/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by-sa/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2201.06384

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