| Enriching word vectors with subword information P Bojanowski, E Grave, A Joulin, T Mikolov Transactions of the association for computational linguistics 5, 135-146, 2017 | 13561 | 2017 |
| Llama: Open and efficient foundation language models H Touvron, T Lavril, G Izacard, X Martinet, MA Lachaux, T Lacroix, ... arXiv preprint arXiv:2302.13971, 2023 | 12416 | 2023 |
| Unsupervised cross-lingual representation learning at scale A Conneau arXiv preprint arXiv:1911.02116, 2019 | 6739 | 2019 |
| Bag of tricks for efficient text classification A Joulin, E Grave, P Bojanowski, T Mikolov arXiv preprint arXiv:1607.01759, 2016 | 6598 | 2016 |
| Learning word vectors for 157 languages E Grave, P Bojanowski, P Gupta, A Joulin, T Mikolov arXiv preprint arXiv:1802.06893, 2018 | 1962 | 2018 |
| Advances in pre-training distributed word representations T Mikolov, E Grave, P Bojanowski, C Puhrsch, A Joulin arXiv preprint arXiv:1712.09405, 2017 | 1845 | 2017 |
| Fasttext. zip: Compressing text classification models A Joulin arXiv preprint arXiv:1612.03651, 2016 | 1772 | 2016 |
| Leveraging passage retrieval with generative models for open domain question answering G Izacard, E Grave arXiv preprint arXiv:2007.01282, 2020 | 1106 | 2020 |
| Parseval networks: Improving robustness to adversarial examples M Cisse, P Bojanowski, E Grave, Y Dauphin, N Usunier International conference on machine learning, 854-863, 2017 | 926 | 2017 |
| Beyond english-centric multilingual machine translation A Fan, S Bhosale, H Schwenk, Z Ma, A El-Kishky, S Goyal, M Baines, ... Journal of Machine Learning Research 22 (107), 1-48, 2021 | 839 | 2021 |
| ResMLP: Feedforward networks for image classification with data-efficient training H Touvron, P Bojanowski, M Caron, M Cord, A El-Nouby, E Grave, ... arXiv preprint arXiv:2105.03404, 2021 | 819* | 2021 |
| Towards unsupervised dense information retrieval with contrastive learning G Izacard, M Caron, L Hosseini, S Riedel, P Bojanowski, A Joulin, ... arXiv preprint arXiv:2112.09118 2 (3), 2021 | 772 | 2021 |
| Colorless green recurrent networks dream hierarchically K Gulordava arXiv preprint arXiv:1803.11138, 2018 | 665 | 2018 |
| Few-shot learning with retrieval augmented language models G Izacard, P Lewis, M Lomeli, L Hosseini, F Petroni, T Schick, ... arXiv preprint arXiv:2208.03299 1 (2), 4, 2022 | 658* | 2022 |
| Reducing transformer depth on demand with structured dropout A Fan, E Grave, A Joulin arXiv preprint arXiv:1909.11556, 2019 | 652 | 2019 |
| CCNet: Extracting high quality monolingual datasets from web crawl data G Wenzek, MA Lachaux, A Conneau, V Chaudhary, F Guzmán, A Joulin, ... arXiv preprint arXiv:1911.00359, 2019 | 650 | 2019 |
| Augmented language models: a survey G Mialon, R Dessì, M Lomeli, C Nalmpantis, R Pasunuru, R Raileanu, ... arXiv preprint arXiv:2302.07842, 2023 | 494 | 2023 |
| Loss in translation: Learning bilingual word mapping with a retrieval criterion A Joulin, P Bojanowski, T Mikolov, H Jégou, E Grave arXiv preprint arXiv:1804.07745, 2018 | 382 | 2018 |
| Improving neural language models with a continuous cache E Grave, A Joulin, N Usunier arXiv preprint arXiv:1612.04426, 2016 | 350 | 2016 |
| Adaptive attention span in transformers S Sukhbaatar, E Grave, P Bojanowski, A Joulin arXiv preprint arXiv:1905.07799, 2019 | 334 | 2019 |
Armand JoulinGoogle DeepMindEmail verificata su google.com
