Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Edouard Grave"'
Autor:
Edouard Grave, Gautier Izacard
Publikováno v:
EACL 2021-16th Conference of the European Chapter of the Association for Computational Linguistics
EACL 2021-16th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kiev, Ukraine. pp.874-880, ⟨10.18653/v1/2021.eacl-main.74⟩
EACL
EACL 2021-16th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kiev, Ukraine. pp.874-880, ⟨10.18653/v1/2021.eacl-main.74⟩
EACL
International audience; Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge. While promising, this approach requires to use models with billions of parameters, which are expensiv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a68099108ebfa4f051283c5eb28d09f
https://hal.archives-ouvertes.fr/hal-03463108/document
https://hal.archives-ouvertes.fr/hal-03463108/document
Autor:
Hugo Touvron, Piotr Bojanowski, Mathilde Caron, Matthieu Cord, Alaaeldin El-Nouby, Edouard Grave, Gautier Izacard, Armand Joulin, Gabriel Synnaeve, Jakob Verbeek, Herve Jegou
We present ResMLP, an architecture built entirely upon multi-layer perceptrons for image classification. It is a simple residual network that alternates (i) a linear layer in which image patches interact, independently and identically across channels
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d039734818b3004f9b4785d6ef946728
Publikováno v:
ACL/IJCNLP (1)
We show that margin-based bitext mining in a multilingual sentence space can be successfully scaled to operate on monolingual corpora of billions of sentences. We use 32 snapshots of a curated common crawl corpus (Wenzel et al, 2019) totaling 71 bill
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33ddb41e90651fb3a62a0f5b524b595b
https://doi.org/10.18653/v1/2021.acl-long.507
https://doi.org/10.18653/v1/2021.acl-long.507
Autor:
Edouard Grave, Veselin Stoyanov, Vishrav Chaudhary, Beliz Gunel, Jingfei Du, Onur Celebi, Michael Auli, Alexis Conneau
Publikováno v:
NAACL-HLT
Unsupervised pre-training has led to much recent progress in natural language understanding. In this paper, we study self-training as another way to leverage unlabeled data through semi-supervised learning. To obtain additional data for a specific ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35d9966a169360a0ecb857f71449e7a5
Autor:
Edouard Grave, Vishrav Chaudhary, Guillaume Wenzek, Luke Zettlemoyer, Kartikay Khandelwal, Veselin Stoyanov, Naman Goyal, Myle Ott, Alexis Conneau, Francisco Guzmán
Publikováno v:
ACL
This paper shows that pretraining multilingual language models at scale leads to significant performance gains for a wide range of cross-lingual transfer tasks. We train a Transformer-based masked language model on one hundred languages, using more t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c85bb0ac4ff2df447a9785930a1bf01d
https://doi.org/10.18653/v1/2020.acl-main.747
https://doi.org/10.18653/v1/2020.acl-main.747
Publikováno v:
ACL (1)
We propose a novel self-attention mechanism that can learn its optimal attention span. This allows us to extend significantly the maximum context size used in Transformer, while maintaining control over their memory footprint and computational time.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cd853bf648ea9fa2d4d3e629e139160
http://arxiv.org/abs/1905.07799
http://arxiv.org/abs/1905.07799
Autor:
Rui Ferreira, Fabrizio Silvestri, Piotr Bojanowski, Edouard Grave, Necati Bora Edizel, Aleksandra Piktus
Publikováno v:
NAACL-HLT (1)
In this paper we present a method to learn word embeddings that are resilient to misspellings. Existing word embeddings have limited applicability to malformed texts, which contain a non-negligible amount of out-of-vocabulary words. We propose a meth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aac1bc23d6e9e02a2b7dd67e23f39dcd
Publikováno v:
ACL (1)
In this paper, we study the problem of hybrid language modeling, that is using models which can predict both characters and larger units such as character ngrams or words. Using such models, multiple potential segmentations usually exist for a given
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d850389f11ba5c9afabc6fbf705c74b0
https://doi.org/10.18653/v1/p19-1143
https://doi.org/10.18653/v1/p19-1143
Publikováno v:
EMNLP
Continuous word representations learned separately on distinct languages can be aligned so that their words become comparable in a common space. Existing works typically solve a least-square regression problem to learn a rotation aligning a small bil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::737f2c99f54b0e6bbfce359b370f46e2
http://arxiv.org/abs/1804.07745
http://arxiv.org/abs/1804.07745
Autor:
Jan Claassen, Kalijah Terilli, Murad Megjhani, Hans-Peter Frey, E. Sander Connolly, Chris H. Wiggins, Edouard Grave, David Roh, Sachin Agarwal, Angela Velazquez, Soojin Park, Noémie Elhadad, J. Michael Schmidt
PURPOSE: To develop and validate a prediction model for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH) using a temporal unsupervised feature engineering approach, demonstrating improved precision over standard features. METHODS:
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::683fa7631f1f79851e83374c00d60207
https://europepmc.org/articles/PMC6681895/
https://europepmc.org/articles/PMC6681895/