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1
Representation Learning for Natural Language Processing
Representation Learning for Natural Language Processing
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Representation Learning for Natural Language Processing

ISBN: 9811555729 ;ISBN: 9789811555725 ;EISBN: 9789811555732 ;EISBN: 9811555737 ;DOI: 10.1007/978-981-15-5573-2 ;OCLC: 1176494182

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2
Resources and benchmark corpora for hate speech detection: a systematic review
Resources and benchmark corpora for hate speech detection: a systematic review
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Resources and benchmark corpora for hate speech detection: a systematic review

Language resources and evaluation, 2021-06, Vol.55 (2), p.477-523 [Peer Reviewed Journal]

The Author(s) 2020 ;The Author(s) 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. ;ISSN: 1574-020X ;EISSN: 1574-0218 ;DOI: 10.1007/s10579-020-09502-8

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3
Representation Learning for Natural Language Processing
Representation Learning for Natural Language Processing
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Representation Learning for Natural Language Processing

ISBN: 9789819916009 ;ISBN: 9819916003 ;ISBN: 9819915996 ;ISBN: 9789819915996 ;DOI: 10.1007/978-981-99-1600-9

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4
Foundation Models for Natural Language Processing: Pre-trained Language Models Integrating Media
Foundation Models for Natural Language Processing: Pre-trained Language Models Integrating Media
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Foundation Models for Natural Language Processing: Pre-trained Language Models Integrating Media

ISBN: 3031231899 ;ISBN: 9783031231902 ;ISBN: 9783031231896 ;ISBN: 3031231902 ;DOI: 10.1007/978-3-031-23190-2

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5
Probing Classifiers: Promises, Shortcomings, and Advances
Probing Classifiers: Promises, Shortcomings, and Advances
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Probing Classifiers: Promises, Shortcomings, and Advances

Computational linguistics - Association for Computational Linguistics, 2022-04, Vol.48 (1), p.207-219 [Peer Reviewed Journal]

2022. This work is published under https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0891-2017 ;EISSN: 1530-9312 ;DOI: 10.1162/coli_a_00422

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6
Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
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Leveraging Pre-trained Checkpoints for Sequence Generation Tasks

Transactions of the Association for Computational Linguistics, 2020-01, Vol.8, p.264-280 [Peer Reviewed Journal]

2020. 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. ;ISSN: 2307-387X ;EISSN: 2307-387X ;DOI: 10.1162/tacl_a_00313

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7
Machine translation for everyone: Empowering users in the age of artificial intelligence
Machine translation for everyone: Empowering users in the age of artificial intelligence
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Machine translation for everyone: Empowering users in the age of artificial intelligence

ISBN: 9783985540457 ;ISBN: 3985540454 ;DOI: 10.5281/zenodo.6653406

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8
A Primer in BERTology: What We Know About How BERT Works
A Primer in BERTology: What We Know About How BERT Works
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A Primer in BERTology: What We Know About How BERT Works

Transactions of the Association for Computational Linguistics, 2020-01, Vol.8, p.842-866 [Peer Reviewed Journal]

2020. 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. ;ISSN: 2307-387X ;EISSN: 2307-387X ;DOI: 10.1162/tacl_a_00349

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9
Digital Humanities, Corpus and Language Technology = Humanidades Digitales, Corpus y Tecnología del Lenguaje: A look from diverse case studies = Una mirada desde diversos casos de estudio
Digital Humanities, Corpus and Language Technology = Humanidades Digitales, Corpus y Tecnología del Lenguaje: A look from diverse case studies = Una mirada desde diversos casos de estudio
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Digital Humanities, Corpus and Language Technology = Humanidades Digitales, Corpus y Tecnología del Lenguaje: A look from diverse case studies = Una mirada desde diversos casos de estudio

ISBN: 9403430230 ;ISBN: 9789403430232 ;DOI: 10.21827/646242d096beb

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10
What BERT Is Not: Lessons from a New Suite of Psycholinguistic Diagnostics for Language Models
What BERT Is Not: Lessons from a New Suite of Psycholinguistic Diagnostics for Language Models
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What BERT Is Not: Lessons from a New Suite of Psycholinguistic Diagnostics for Language Models

Transactions of the Association for Computational Linguistics, 2020-01, Vol.8, p.34-48 [Peer Reviewed Journal]

2020. 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. ;ISSN: 2307-387X ;EISSN: 2307-387X ;DOI: 10.1162/tacl_a_00298

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11
GPT-3: What’s it good for?
GPT-3: What’s it good for?
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GPT-3: What’s it good for?

Natural language engineering, 2021-01, Vol.27 (1), p.113-118 [Peer Reviewed Journal]

Cambridge University Press 2020 ;2020 This article is published under (https://creativecommons.org/licenses/by/3.0/) (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1351-3249 ;EISSN: 1469-8110 ;DOI: 10.1017/S1351324920000601

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12
Urdu language processing: a survey
Urdu language processing: a survey
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Urdu language processing: a survey

The Artificial intelligence review, 2017-03, Vol.47 (3), p.279-311 [Peer Reviewed Journal]

Springer Science+Business Media Dordrecht 2016 ;COPYRIGHT 2017 Springer ;Artificial Intelligence Review is a copyright of Springer, 2017. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-016-9482-x

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13
Parameter-efficient fine-tuning of large-scale pre-trained language models
Parameter-efficient fine-tuning of large-scale pre-trained language models
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Parameter-efficient fine-tuning of large-scale pre-trained language models

Nature machine intelligence, 2023-03, Vol.5 (3), p.220-235 [Peer Reviewed Journal]

The Author(s) 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. ;ISSN: 2522-5839 ;EISSN: 2522-5839 ;DOI: 10.1038/s42256-023-00626-4

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14
The handbook of computational linguistics and natural language processing
The handbook of computational linguistics and natural language processing
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The handbook of computational linguistics and natural language processing

ISBN: 9781444324051 ;ISBN: 1444324055 ;ISBN: 9781405155816 ;ISBN: 1405155817 ;ISBN: 9781118347188 ;ISBN: 1118347188 ;ISBN: 9781444324044 ;ISBN: 1444324047 ;EISBN: 1118448677 ;EISBN: 9781118448670 ;EISBN: 9781444324051 ;EISBN: 1444324055 ;DOI: 10.1002/9781444324044 ;OCLC: 927508167 ;OCLC: 657621904 ;LCCallNum: P98.H346 2010

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15
Shared computational principles for language processing in humans and deep language models
Shared computational principles for language processing in humans and deep language models
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Shared computational principles for language processing in humans and deep language models

Nature neuroscience, 2022-03, Vol.25 (3), p.369-380 [Peer Reviewed Journal]

2022. The Author(s). ;The Author(s) 2022. 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. ;The Author(s) 2022 ;ISSN: 1097-6256 ;EISSN: 1546-1726 ;DOI: 10.1038/s41593-022-01026-4 ;PMID: 35260860

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16
Revealing Media Bias in News Articles: NLP Techniques for Automated Frame Analysis
Revealing Media Bias in News Articles: NLP Techniques for Automated Frame Analysis
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Revealing Media Bias in News Articles: NLP Techniques for Automated Frame Analysis

ISBN: 9783031176937 ;ISBN: 3031176936 ;DOI: 10.1007/978-3-031-17693-7

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17
SummaC : Re-Visiting NLI-based Models for Inconsistency Detection in Summarization
SummaC : Re-Visiting NLI-based Models for Inconsistency Detection in Summarization
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SummaC : Re-Visiting NLI-based Models for Inconsistency Detection in Summarization

Transactions of the Association for Computational Linguistics, 2022-02, Vol.10, p.163-177 [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. ;ISSN: 2307-387X ;EISSN: 2307-387X ;DOI: 10.1162/tacl_a_00453

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18
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP
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Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP

Transactions of the Association for Computational Linguistics, 2021-12, Vol.9, p.1408-1424 [Peer Reviewed Journal]

2021. 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. ;ISSN: 2307-387X ;EISSN: 2307-387X ;DOI: 10.1162/tacl_a_00434

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19
Analysis Methods in Neural Language Processing: A Survey
Analysis Methods in Neural Language Processing: A Survey
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Analysis Methods in Neural Language Processing: A Survey

Transactions of the Association for Computational Linguistics, 2019-01, Vol.7, p.49-72 [Peer Reviewed Journal]

2019. 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. ;ISSN: 2307-387X ;EISSN: 2307-387X ;DOI: 10.1162/tacl_a_00254

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20
Break It Down: A Question Understanding Benchmark
Break It Down: A Question Understanding Benchmark
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Break It Down: A Question Understanding Benchmark

Transactions of the Association for Computational Linguistics, 2020-01, Vol.8, p.183 [Peer Reviewed Journal]

2020. 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. ;ISSN: 2307-387X ;EISSN: 2307-387X ;DOI: 10.1162/tacl_a_00309

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