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We introduce MTG, a new benchmark suite for training and evaluating multilingual text generation.
Cross-lingual language model pretraining
Guillaume Lample and Alexis Conneau. 2019 · 1901
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Bertscore: Evaluating text generation with bert
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Massively multilingual neural machine translation in the wild: Findings and challenges
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Bagging predictors
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Automatic summarization , volume 3
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Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
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Mkqa: A linguistically diverse benchmark for multilingual open domain question answering
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mt5: A massively multilingual pre-trained text-to-text transformer
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Abstractive text summarization using sequence-to-sequence rnns and beyond
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Junnan Zhu, Qian Wang, Yining Wang, Yu Zhou, Jiajun Zhang, Shaonan Wang, and Chengqing Zong. 2019 · 2019
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On the cross-lingual transferability of monolingual representations
Mikel Artetxe, Sebastian Ruder, and Dani Yogatama. 2020 · 2020
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Wiki-40b: Multilingual language model dataset
Mandy Guo, Zihang Dai, Denny Vrandečić, and Rami Al-Rfou. 2020 · 2020
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Xtreme: A massively multilingual multi-task benchmark for evaluating cross-lingual generalisation
Junjie Hu, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan Firat, and Melvin Johnson. 2020 · 2020
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X-factr: Multilingual factual knowledge retrieval from pretrained language models
Zhengbao Jiang, Antonios Anastasopoulos, Jun Araki, Haibo Ding, and Graham Neubig. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
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The gem benchmark: Natural language generation, its evaluation and metrics
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