| Supervised Learning of Universal Sentence Representations from Natural Language Inference Data A Conneau, D Kiela, H Schwenk, L Barrault, A Bordes EMNLP 2017, 2017 | 1268 | 2017 |
| Very deep convolutional networks for text classification A Conneau, H Schwenk, L Barrault, Y Lecun EACL 2017, 2016 | 949* | 2016 |
| Word Translation Without Parallel Data A Conneau, G Lample, MA Ranzato, L Denoyer, H Jégou ICLR 2018, 2017 | 886 | 2017 |
| Cross-lingual Language Model Pretraining A Conneau, G Lample NeurIPS 2019, 2019 | 761* | 2019 |
| Unsupervised Machine Translation Using Monolingual Corpora Only G Lample, A Conneau, L Denoyer, MA Ranzato ICLR 2018, 2017 | 645 | 2017 |
| Unsupervised Cross-lingual Representation Learning at Scale A Conneau, K Khandelwal, N Goyal, V Chaudhary, G Wenzek, F Guzmán, ... ACL 2020, 2019 | 398 | 2019 |
| Phrase-Based & Neural Unsupervised Machine Translation G Lample, M Ott, A Conneau, L Denoyer, MA Ranzato EMNLP 2018, 2018 | 398 | 2018 |
| What you can cram into a single vector: Probing sentence embeddings for linguistic properties A Conneau, G Kruszewski, G Lample, L Barrault, M Baroni ACL 2018, 2018 | 335 | 2018 |
| XNLI: Evaluating Cross-lingual Sentence Representations A Conneau, G Lample, R Rinott, A Williams, SR Bowman, H Schwenk, ... EMNLP 2018, 2018 | 305 | 2018 |
| SentEval: An Evaluation Toolkit for Universal Sentence Representations A Conneau, D Kiela LREC 2018, 2018 | 205 | 2018 |
| Product embeddings using side-information for recommendation F Vasile, E Smirnova, A Conneau WWW 2016, 2016 | 157* | 2016 |
| Learning visually grounded sentence representations D Kiela, A Conneau, A Jabri, M Nickel NAACL 2018, 2017 | 47 | 2017 |
| Emerging Cross-lingual Structure in Pretrained Language Models A Conneau, S Wu, H Li, L Zettlemoyer, V Stoyanov ACL 2020, 2019 | 42* | 2019 |
| Ccnet: Extracting high quality monolingual datasets from web crawl data G Wenzek, MA Lachaux, A Conneau, V Chaudhary, F Guzman, A Joulin, ... LREC 2020, 2019 | 41 | 2019 |
| Unsupervised cross-lingual representation learning for speech recognition A Conneau, A Baevski, R Collobert, A Mohamed, M Auli arXiv preprint arXiv:2006.13979, 2020 | 13 | 2020 |
| Self-training improves pre-training for natural language understanding J Du, E Grave, B Gunel, V Chaudhary, O Celebi, M Auli, V Stoyanov, ... arXiv preprint arXiv:2010.02194, 2020 | 4 | 2020 |
| Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning B Gunel, J Du, A Conneau, V Stoyanov ICLR 2021, 2020 | 2 | 2020 |
| Self-training and Pre-training are Complementary for Speech Recognition Q Xu, A Baevski, T Likhomanenko, P Tomasello, A Conneau, R Collobert, ... arXiv preprint arXiv:2010.11430, 2020 | 2 | 2020 |
| Multilingual Speech Translation with Efficient Finetuning of Pretrained Models X Li, C Wang, Y Tang, C Tran, Y Tang, J Pino, A Baevski, A Conneau, ... arXiv e-prints, arXiv: 2010.12829, 2020 | 1 | 2020 |
Guillaume LampleResearch Scientist, Facebook AI ResearchVerified email at fb.com
