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Alexis Conneau
Researcher at Facebook
Publications - 45
Citations - 16481
Alexis Conneau is an academic researcher from Facebook. The author has contributed to research in topics: Language model & Sentence. The author has an hindex of 29, co-authored 45 publications receiving 10895 citations.
Papers
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Proceedings ArticleDOI
Unsupervised Cross-lingual Representation Learning at Scale
Alexis Conneau,Kartikay Khandelwal,Naman Goyal,Vishrav Chaudhary,Guillaume Wenzek,Francisco Guzmán,Edouard Grave,Myle Ott,Luke Zettlemoyer,Veselin Stoyanov +9 more
TL;DR: It is shown that pretraining multilingual language models at scale leads to significant performance gains for a wide range of cross-lingual transfer tasks, and the possibility of multilingual modeling without sacrificing per-language performance is shown for the first time.
Proceedings ArticleDOI
Supervised learning of universal sentence representations from natural language inference data
TL;DR: This article showed how universal sentence representations trained using the supervised data of the Stanford Natural Language Inference datasets can consistently outperform unsupervised methods like SkipThought vectors on a wide range of transfer tasks.
Posted Content
Cross-lingual Language Model Pretraining.
Guillaume Lample,Alexis Conneau +1 more
TL;DR: This work proposes two methods to learn cross-lingual language models (XLMs): one unsupervised that only relies on monolingual data, and one supervised that leverages parallel data with a new cross-lingsual language model objective.
Proceedings Article
Word translation without parallel data
TL;DR: It is shown that a bilingual dictionary can be built between two languages without using any parallel corpora, by aligning monolingual word embedding spaces in an unsupervised way.
Proceedings ArticleDOI
Very deep convolutional networks for text classification
TL;DR: Very deep convolutional networks (VDCNN) as mentioned in this paper have been applied to text classification. And they have achieved state-of-the-art performance on several public text classification tasks.