| 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 | 14219 | 2023 |
| Neural architectures for named entity recognition G Lample, M Ballesteros, S Subramanian, K Kawakami, C Dyer NAACL 2016, 2016 | 5608 | 2016 |
| Mistral 7B. arXiv 2023 AQ Jiang, A Sablayrolles, A Mensch, C Bamford, DS Chaplot, D Casas, ... arXiv preprint arXiv:2310.06825, 2024 | 4323* | 2024 |
| Cross-lingual language model pretraining G Lample, A Conneau NIPS 2019, 2019 | 3457* | 2019 |
| Word translation without parallel data G Lample, A Conneau, MA Ranzato, L Denoyer, H Jégou ICLR 2018, 2018 | 1988* | 2018 |
| Mixtral of experts AQ Jiang, A Sablayrolles, A Roux, A Mensch, B Savary, C Bamford, ... arXiv preprint arXiv:2401.04088, 2024 | 1679 | 2024 |
| XNLI: Evaluating cross-lingual sentence representations A Conneau, G Lample, R Rinott, A Williams, SR Bowman, H Schwenk, ... EMNLP 2018, 2018 | 1486 | 2018 |
| Unsupervised Machine Translation Using Monolingual Corpora Only G Lample, A Conneau, L Denoyer, MA Ranzato ICLR 2018, 2018 | 1357 | 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 | 1063 | 2018 |
| Phrase-Based & Neural Unsupervised Machine Translation G Lample, M Ott, A Conneau, L Denoyer, MA Ranzato EMNLP 2018, 2018 | 812 | 2018 |
| Playing FPS Games with Deep Reinforcement Learning. G Lample, DS Chaplot AAAI 2017, 2017 | 807 | 2017 |
| Fader Networks: Manipulating Images by Sliding Attributes G Lample, N Zeghidour, N Usunier, A Bordes, L Denoyer, MA Ranzato NIPS 2017, 2017 | 633 | 2017 |
| Deep learning for symbolic mathematics G Lample, F Charton ICLR 2020, 2019 | 567 | 2019 |
| Unsupervised translation of programming languages MA Lachaux, B Roziere, L Chanussot, G Lample arXiv preprint arXiv:2006.03511, 2020 | 454* | 2020 |
| Multiple-Attribute Text Rewriting G Lample, S Subramanian, E Smith, L Denoyer, YL Boureau ICLR 2019, 2018 | 358* | 2018 |
| Massively multilingual word embeddings W Ammar, G Mulcaire, Y Tsvetkov, G Lample, C Dyer, NA Smith arXiv preprint arXiv:1602.01925, 2016 | 356 | 2016 |
| The flores evaluation datasets for low-resource machine translation: Nepali-english and sinhala-english F Guzmán, PJ Chen, M Ott, J Pino, G Lample, P Koehn, V Chaudhary, ... arXiv preprint arXiv:1902.01382, 2019 | 327 | 2019 |
| Evaluation of word vector representations by subspace alignment Y Tsvetkov, M Faruqui, W Ling, G Lample, C Dyer EMNLP 2015, 2015 | 197 | 2015 |
| End-to-end symbolic regression with transformers PA Kamienny, S d'Ascoli, G Lample, F Charton Advances in Neural Information Processing Systems 35, 10269-10281, 2022 | 194 | 2022 |
| Dobf: A deobfuscation pre-training objective for programming languages B Roziere, MA Lachaux, M Szafraniec, G Lample arXiv preprint arXiv:2102.07492, 2021 | 165* | 2021 |
Sandeep SubramanianMistral AI在 umontreal.ca 的电子邮件经过验证
