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1
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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2
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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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
VQA: Visual Question Answering: www.visualqa.org
VQA: Visual Question Answering: www.visualqa.org
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VQA: Visual Question Answering: www.visualqa.org

International journal of computer vision, 2017-05, Vol.123 (1), p.4-31 [Peer Reviewed Journal]

Springer Science+Business Media New York 2016 ;International Journal of Computer Vision is a copyright of Springer, 2017. ;ISSN: 0920-5691 ;EISSN: 1573-1405 ;DOI: 10.1007/s11263-016-0966-6

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5
Characterization inference based on joint-optimization of multi-layer semantics and deep fusion matching network
Characterization inference based on joint-optimization of multi-layer semantics and deep fusion matching network
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Characterization inference based on joint-optimization of multi-layer semantics and deep fusion matching network

PeerJ. Computer science, 2022-04, Vol.8, p.e908-e908, Article e908 [Peer Reviewed Journal]

2022 Zheng and Yin. ;COPYRIGHT 2022 PeerJ. Ltd. ;2022 Zheng and Yin. This is an open access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 Zheng and Yin 2022 Zheng and Yin ;ISSN: 2376-5992 ;EISSN: 2376-5992 ;DOI: 10.7717/peerj-cs.908 ;PMID: 35494798

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6
Natural language processing: state of the art, current trends and challenges
Natural language processing: state of the art, current trends and challenges
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Natural language processing: state of the art, current trends and challenges

Multimedia tools and applications, 2023-01, Vol.82 (3), p.3713-3744 [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.. corrected publication 2022 ;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.corrected publication 2022. ;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. corrected publication 2022. ;The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, corrected publication 2022Springer 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. ;ISSN: 1380-7501 ;EISSN: 1573-7721 ;DOI: 10.1007/s11042-022-13428-4 ;PMID: 35855771

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7
Trick Me If You Can: Human-in-the-Loop Generation of Adversarial Examples for Question Answering
Trick Me If You Can: Human-in-the-Loop Generation of Adversarial Examples for Question Answering
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Trick Me If You Can: Human-in-the-Loop Generation of Adversarial Examples for Question Answering

Transactions of the Association for Computational Linguistics, 2019-11, Vol.7, p.387-401 [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_00279

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8
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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9
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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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
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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13
Representation Learning for Natural Language Processing
Representation Learning for Natural Language Processing
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Book 		Add to My Research

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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14
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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15
Commentary: Measuring Language Change Through Natural Language Samples
Commentary: Measuring Language Change Through Natural Language Samples
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Commentary: Measuring Language Change Through Natural Language Samples

Journal of autism and developmental disorders, 2020-07, Vol.50 (7), p.2287-2306 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2018 ;COPYRIGHT 2020 Springer ;Springer Science+Business Media, LLC, part of Springer Nature 2018. ;ISSN: 0162-3257 ;EISSN: 1573-3432 ;DOI: 10.1007/s10803-018-3628-4 ;PMID: 29873016

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16
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
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Revolutionizing healthcare: the role of artificial intelligence in clinical practice

BMC medical education, 2023-09, Vol.23 (1), p.1-689, Article 689 [Peer Reviewed Journal]

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. ;BioMed Central Ltd., part of Springer Nature 2023 ;ISSN: 1472-6920 ;EISSN: 1472-6920 ;DOI: 10.1186/s12909-023-04698-z ;PMID: 37740191

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17
Sentence Representation Method Based on Multi-Layer Semantic Network
Sentence Representation Method Based on Multi-Layer Semantic Network
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Sentence Representation Method Based on Multi-Layer Semantic Network

Applied sciences, 2021-02, Vol.11 (3), p.1316 [Peer Reviewed Journal]

2021. This work is licensed under http://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. ;2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2076-3417 ;EISSN: 2076-3417 ;DOI: 10.3390/app11031316

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18
Machine learning, natural language programming, and electronic health records: The next step in the artificial intelligence journey?
Machine learning, natural language programming, and electronic health records: The next step in the artificial intelligence journey?
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Machine learning, natural language programming, and electronic health records: The next step in the artificial intelligence journey?

Journal of allergy and clinical immunology, 2018-06, Vol.141 (6), p.2019 [Peer Reviewed Journal]

EISSN: 1097-6825 ;DOI: 10.1016/j.jaci.2018.02.025 ;PMID: 29518424

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19
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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20
Personality, gender, and age in the language of social media: the open-vocabulary approach
Personality, gender, and age in the language of social media: the open-vocabulary approach
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Personality, gender, and age in the language of social media: the open-vocabulary approach

PloS one, 2013-09, Vol.8 (9), p.e73791-e73791 [Peer Reviewed Journal]

COPYRIGHT 2013 Public Library of Science ;2013 Schwartz et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2013 Schwartz et al 2013 Schwartz et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0073791 ;PMID: 24086296

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