| 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 | 14206 | 2023 |
| Llama 2: Open foundation and fine-tuned chat models H Touvron, L Martin, K Stone, P Albert, A Almahairi, Y Babaei, ... arXiv preprint arXiv:2307.09288, 2023 | 13782 | 2023 |
| Training data-efficient image transformers & distillation through attention H Touvron, M Cord, M Douze, F Massa, A Sablayrolles, H Jégou International conference on machine learning, 10347-10357, 2021 | 8120 | 2021 |
| Emerging properties in self-supervised vision transformers M Caron, H Touvron, I Misra, H Jégou, J Mairal, P Bojanowski, A Joulin Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021 | 6572 | 2021 |
| The Llama 3 Herd of Models AI Meta arXiv preprint arXiv:2407.21783, 2024 | 4106* | 2024 |
| Code llama: Open foundation models for code B Roziere, J Gehring, F Gloeckle, S Sootla, I Gat, XE Tan, Y Adi, J Liu, ... arXiv preprint arXiv:2308.12950, 2023 | 1953 | 2023 |
| Going deeper with image transformers H Touvron, M Cord, A Sablayrolles, G Synnaeve, H Jégou Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021 | 1270 | 2021 |
| LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference B Graham, A El-Nouby, H Touvron, P Stock, A Joulin, H Jégou, M Douze Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021 | 1013* | 2021 |
| Convit: Improving vision transformers with soft convolutional inductive biases S d'Ascoli, H Touvron, M Leavitt, A Morcos, G Biroli, L Sagun International Conference on Machine Learning, 2021 | 971 | 2021 |
| Resmlp: Feedforward networks for image classification with data-efficient training H Touvron, P Bojanowski, M Caron, M Cord, A El-Nouby, E Grave, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 865* | 2021 |
| Fixing the train-test resolution discrepancy H Touvron, A Vedaldi, M Douze, H Jégou Advances in neural information processing systems 32, 2019 | 683 | 2019 |
| XCiT: Cross-Covariance Image Transformers A El-Nouby, H Touvron, M Caron, P Bojanowski, M Douze, A Joulin, ... Advances in Neural Information Processing Systems, 2021 | 626* | 2021 |
| Resnet strikes back: An improved training procedure in timm R Wightman, H Touvron, H Jégou NeurIPS 2021 Workshop on ImageNet: Past, Present, and Future, 2021 | 575 | 2021 |
| Deit iii: Revenge of the vit H Touvron, M Cord, H Jégou Proceedings of the European conference on computer vision (ECCV), 2022 | 463 | 2022 |
| Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv: 2307.0928810. 48550 H Touvron arXiv preprint arXiv.2307.09288, 2023 | 169* | 2023 |
| Are large-scale datasets necessary for self-supervised pre-training? A El-Nouby, G Izacard, H Touvron, I Laptev, H Jegou, E Grave arXiv preprint arXiv:2112.10740, 2021 | 165 | 2021 |
| Three things everyone should know about Vision Transformers H Touvron, M Cord, A El-Nouby, J Verbeek, H Jégou Proceedings of the European conference on computer vision (ECCV), 2022 | 147 | 2022 |
| LLaMA: open and efficient foundation language models. DOI: 10.48550 H Touvron, T Lavril, G Izacard, X Martinet, MA Lachaux, T Lacroix, ... arXiv preprint arXiv.2302.13971 2302, 2023 | 102* | 2023 |
| Grafit: Learning fine-grained image representations with coarse labels H Touvron, A Sablayrolles, M Douze, M Cord, H Jégou Proceedings of the IEEE/CVF international conference on computer vision, 874-884, 2021 | 86 | 2021 |
| Llama 2: Open foundation and fine-tuned chat models T Hugo, M Louis, S Kevin, A Peter, A Amjad, B Yasmine, B Nikolay, ... arXiv preprint arXiv:2307.09288, 2023 | 85 | 2023 |
Hervé JégouFAIRVerified email at meta.com
