“BERTology”如何改变了意大利NLP的技术水平

Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI:10.4000/books.aaccademia.8920

F. Tamburini

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引用次数: 10

摘要

上下文化词嵌入的使用使得几乎所有自然语言处理(NLP)应用程序的性能都有了相应的提高。最近，学者们可以使用一些专门为意大利语开发的新模型。这项工作旨在评估这些模型在提高应用性能方面的影响，为意大利建立一些基础NLP任务的新技术。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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How "BERTology" Changed the State-of-the-Art also for Italian NLP

The use of contextualised word embeddings allowed for a relevant performance increase for almost all Natural Language Processing (NLP) applications. Recently some new models especially developed for Italian became available to scholars. This work aims at evaluating the impact of these models in enhancing application performance for Italian establishing the new state-of-the-art for some fundamental NLP tasks.

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Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

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