mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer
Linting Xue,Noah Constant,Adam Roberts,Mihir Kale,Rami Al-Rfou,Aditya Siddhant,Aditya Barua,Colin Raffel +7 more
- pp 483-498
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TLDR
This paper proposed a multilingual variant of T5, mT5, which was pre-trained on a new Common Crawl-based dataset covering 101 languages and achieved state-of-the-art performance on many multilingual benchmarks.Abstract:
The recent “Text-to-Text Transfer Transformer” (T5) leveraged a unified text-to-text format and scale to attain state-of-the-art results on a wide variety of English-language NLP tasks. In this paper, we introduce mT5, a multilingual variant of T5 that was pre-trained on a new Common Crawl-based dataset covering 101 languages. We detail the design and modified training of mT5 and demonstrate its state-of-the-art performance on many multilingual benchmarks. We also describe a simple technique to prevent “accidental translation” in the zero-shot setting, where a generative model chooses to (partially) translate its prediction into the wrong language. All of the code and model checkpoints used in this work are publicly available.read more
Citations
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Journal ArticleDOI
AraConv: Developing an Arabic Task-Oriented Dialogue System Using Multi-Lingual Transformer Model mT5
Ahlam Fuad,Maha Al-Yahya +1 more
TL;DR: This study introduces the first Arabic end-to-end generative model for task-oriented DS (AraConv), which uses the multi-lingual transformer model mT5 with different settings, and indicates the AraConv model performed better in the joint-training setting than in the mono-lingually setting.
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Federated Learning of Gboard Language Models with Differential Privacy
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Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness
Caner Hazirbas,Yejin Bang,Tiezheng Yu,Parisa Assar,Bilal Porgali,Vitor Albiero,Stefan Hermanek,Jacqueline Pan,Emily McReynolds,Miranda Bogen,Pascale Fung,Cristian Canton-Ferrer +11 more
TL;DR: In this paper , a large consent-driven dataset with a comprehensive list of categories and subcategories for Casual Conversations v2 has been proposed to measure AI algorithmic bias and robustness.
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Smart Analysis of Economics Sentiment in Spanish Based on Linguistic Features and Transformers
TL;DR: In this paper , the authors explored the impact of the combination of different feature sets in the accuracy of Sentiment Analysis in Spanish financial texts and obtained the best results with a weighted F1-score of 73.15880%.
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Graphemic Normalization of the Perso-Arabic Script
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