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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
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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3
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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4
Commentary: Using Language to Improve Health
Commentary: Using Language to Improve Health
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Commentary: Using Language to Improve Health

Journal of service research : JSR, 2023-11, Vol.26 (4), p.514-516 [Peer Reviewed Journal]

The Author(s) 2023 ;ISSN: 1094-6705 ;EISSN: 1552-7379 ;DOI: 10.1177/10946705231194075

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5
A Primer on Neural Network Models for Natural Language Processing
A Primer on Neural Network Models for Natural Language Processing
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A Primer on Neural Network Models for Natural Language Processing

The Journal of artificial intelligence research, , Vol.57, p.345-420 [Peer Reviewed Journal]

2016. 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.4992

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6
ProtGPT2 is a deep unsupervised language model for protein design
ProtGPT2 is a deep unsupervised language model for protein design
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ProtGPT2 is a deep unsupervised language model for protein design

Nature communications, 2022-07, Vol.13 (1), p.4348-4348, Article 4348 [Peer Reviewed Journal]

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: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-022-32007-7 ;PMID: 35896542

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7
Learning to Prompt for Vision-Language Models
Learning to Prompt for Vision-Language Models
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Learning to Prompt for Vision-Language Models

International journal of computer vision, 2022-09, Vol.130 (9), p.2337-2348 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;COPYRIGHT 2022 Springer ;ISSN: 0920-5691 ;EISSN: 1573-1405 ;DOI: 10.1007/s11263-022-01653-1

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8
A large language model for electronic health records
A large language model for electronic health records
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A large language model for electronic health records

NPJ digital medicine, 2022-12, Vol.5 (1), p.194-194, Article 194 [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: 2398-6352 ;EISSN: 2398-6352 ;DOI: 10.1038/s41746-022-00742-2 ;PMID: 36572766

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9
A comparative study of pretrained language models for long clinical text
A comparative study of pretrained language models for long clinical text
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A comparative study of pretrained language models for long clinical text

Journal of the American Medical Informatics Association : JAMIA, 2023-01, Vol.30 (2), p.340-347 [Peer Reviewed Journal]

The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com. ;The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com 2022 ;ISSN: 1067-5027 ;EISSN: 1527-974X ;DOI: 10.1093/jamia/ocac225 ;PMID: 36451266

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10
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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11
Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3)
Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3)
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Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3)

Ethics in science and environmental politics ESEP, 2021, Vol.21, p.17-23 [Peer Reviewed Journal]

Copyright Inter-Research Science Center 2021 ;ISSN: 1863-5415 ;EISSN: 1611-8014 ;DOI: 10.3354/esep00195

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12
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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13
Can artificial intelligence help for scientific writing?
Can artificial intelligence help for scientific writing?
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Can artificial intelligence help for scientific writing?

Critical care (London, England), 2023-02, Vol.27 (1), p.75-75, Article 75 [Peer Reviewed Journal]

2023. The Author(s). ;COPYRIGHT 2023 BioMed Central Ltd. ;2023. This work is licensed 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) 2023 ;ISSN: 1364-8535 ;EISSN: 1466-609X ;DOI: 10.1186/s13054-023-04380-2 ;PMID: 36841840

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14
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
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Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations

International journal of computer vision, 2017-05, Vol.123 (1), p.32-73 [Peer Reviewed Journal]

The Author(s) 2017 ;COPYRIGHT 2017 Springer ;International Journal of Computer Vision is a copyright of Springer, 2017. ;ISSN: 0920-5691 ;EISSN: 1573-1405 ;DOI: 10.1007/s11263-016-0981-7

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15
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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16
Transformer models for text-based emotion detection: a review of BERT-based approaches
Transformer models for text-based emotion detection: a review of BERT-based approaches
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Transformer models for text-based emotion detection: a review of BERT-based approaches

The Artificial intelligence review, 2021-12, Vol.54 (8), p.5789-5829 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature 2021 ;COPYRIGHT 2021 Springer ;The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature 2021. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-021-09958-2

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17
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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18
MT-clinical BERT: scaling clinical information extraction with multitask learning
MT-clinical BERT: scaling clinical information extraction with multitask learning
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Article 		Add to My Research

MT-clinical BERT: scaling clinical information extraction with multitask learning

Journal of the American Medical Informatics Association : JAMIA, 2021-09, Vol.28 (10), p.2108-2115 [Peer Reviewed Journal]

The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com. ;The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com 2021 ;ISSN: 1527-974X ;ISSN: 1067-5027 ;EISSN: 1527-974X ;DOI: 10.1093/jamia/ocab126 ;PMID: 34333635

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19
ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health
ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health
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ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health

Frontiers in public health, 2023-04, Vol.11, p.1166120-1166120 [Peer Reviewed Journal]

Copyright © 2023 De Angelis, Baglivo, Arzilli, Privitera, Ferragina, Tozzi and Rizzo. ;Copyright © 2023 De Angelis, Baglivo, Arzilli, Privitera, Ferragina, Tozzi and Rizzo. 2023 De Angelis, Baglivo, Arzilli, Privitera, Ferragina, Tozzi and Rizzo ;ISSN: 2296-2565 ;EISSN: 2296-2565 ;DOI: 10.3389/fpubh.2023.1166120 ;PMID: 37181697

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20
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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