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Controllable sentence simplification with a unified text-to-text transfer transformer

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dc.contributor.author Sheang, Kim Cheng
dc.contributor.author Saggion, Horacio
dc.date.accessioned 2022-09-15T07:17:17Z
dc.date.available 2022-09-15T07:17:17Z
dc.date.issued 2021
dc.identifier.citation Sheang KC, Saggion H. Controllable sentence simplification with a unified text-to-text transfer transformer. In: Proceedings of the 14th International Conference on Natural Language Generation (INLG); 2021 Sep 20-24; Aberdeen, Scotland, UK. Aberdeen: Association for Computational Linguistics; 2021. p. 341-52.
dc.identifier.uri http://hdl.handle.net/10230/54079
dc.description Comunicació presentada a: 14th International Conference on Natural Language Generation (INLG), celebrat del 20 al 24 de setembre de 2021, a Aberdeen, Escòcia, Regne Unit.
dc.description.abstract Recently, a large pre-trained language model called T5 (A Unified Text-to-Text Transfer Transformer) has achieved state-of-the-art performance in many NLP tasks. However, no study has been found using this pre-trained model on Text Simplification. Therefore in this paper, we explore the use of T5 fine-tuning on Text Simplification combining with a controllable mechanism to regulate the system outputs that can help generate adapted text for different target audiences. Our experiments show that our model achieves remarkable results with gains of between +0.69 and +1.41 over the current state-of-the-art (BART+ACCESS). We argue that using a pre-trained model such as T5, trained on several tasks with large amounts of data, can help improve Text Simplification.
dc.description.sponsorship We acknowledge support from the project Context-aware Multilingual Text Simplifcation (ConMuTeS) PID2019-109066GBI00/AEI/10.13039/501100011033 awarded by Ministerio de Ciencia, Innovacion y Universidades ´ (MCIU) and by Agencia Estatal de Investigacion´ (AEI) of Spain. Also, we would like to thank the three anonymous reviewers for their insightful suggestions.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher ACL (Association for Computational Linguistics)
dc.relation.ispartof Proceedings of the 14th International Conference on Natural Language Generation (INLG); 2021 Sep 20-24; Aberdeen, Scotland, UK. Aberdeen: Association for Computational Linguistics; 2021.
dc.rights © ACL, Creative Commons Attribution 4.0 License
dc.title Controllable sentence simplification with a unified text-to-text transfer transformer
dc.type info:eu-repo/semantics/conferenceObject
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-109
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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