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FedQAS: Privacy-Aware Machine Reading Comprehension with Federated Learning
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In: Applied Sciences; Volume 12; Issue 6; Pages: 3130 (2022)
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Abstract:
Machine reading comprehension (MRC) of text data is a challenging task in Natural Language Processing (NLP), with a lot of ongoing research fueled by the release of the Stanford Question Answering Dataset (SQuAD) and Conversational Question Answering (CoQA). It is considered to be an effort to teach computers how to “understand” a text, and then to be able to answer questions about it using deep learning. However, until now, large-scale training on private text data and knowledge sharing has been missing for this NLP task. Hence, we present FedQAS, a privacy-preserving machine reading system capable of leveraging large-scale private data without the need to pool those datasets in a central location. The proposed approach combines transformer models and federated learning technologies. The system is developed using the FEDn framework and deployed as a proof-of-concept alliance initiative. FedQAS is flexible, language-agnostic, and allows intuitive participation and execution of local model training. In addition, we present the architecture and implementation of the system, as well as provide a reference evaluation based on the SQuAD dataset, to showcase how it overcomes data privacy issues and enables knowledge sharing between alliance members in a Federated learning setting.
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Keyword:
data privacy; federated learning; machine reading comprehension; natural language processing; question answering; transformer
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URL: https://doi.org/10.3390/app12063130
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2 |
Neural-based Knowledge Transfer in Natural Language Processing
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English machine reading comprehension: new approaches to answering multiple-choice questions
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Dzendzik, Daria. - : Dublin City University. School of Computing, 2021. : Dublin City University. ADAPT, 2021
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In: Dzendzik, Daria (2021) English machine reading comprehension: new approaches to answering multiple-choice questions. PhD thesis, Dublin City University. (2021)
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A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images ...
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A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images ...
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A Multiple-Choice Machine Reading Comprehension Model with Multi-Granularity Semantic Reasoning
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In: Applied Sciences ; Volume 11 ; Issue 17 (2021)
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11 |
Enhance Text-to-Text Transfer Transformer with Generated Questions for Thai Question Answering
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In: Applied Sciences ; Volume 11 ; Issue 21 (2021)
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12 |
English Machine Reading Comprehension Datasets: A Survey ; Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
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A Reception Study of Machine-Translated Easy Language Text by Individuals with Reading Difficulties
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In: 3rd International Conference on Translation, Interpreting and Cognition (ICTIC3) (2021) (2021)
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Cross-lingual and cross-domain evaluation of Machine Reading Comprehension with Squad and CALOR-Quest corpora
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In: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) ; LREC 2020 ; https://hal.archives-ouvertes.fr/hal-02973245 ; LREC 2020, May 2020, MARSEILLE, France. pp.5491-5497 ; https://lrec2020.lrec-conf.org/en/ (2020)
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Assessment of Word-Level Neural Language Models for Sentence Completion
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In: Applied Sciences ; Volume 10 ; Issue 4 (2020)
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Q. Can Knowledge Graphs be used to Answer Boolean Questions? A. It's complicated! ; First Workshop on Insights from Negative Results in NLP
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Vogel, Carl. - : Association for Computational Linguistics, 2020
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Using Machine Learning to Predict Children’s Reading Comprehension from Lexical and Syntactic Features Extracted from Spoken and Written Language
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Advances in deep learning methods for speech recognition and understanding
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