| Leveraging passage retrieval with generative models for open domain question answering G Izacard, E Grave Proceedings of the 16th Conference of the European Chapter of the …, 2020 | 339 | 2020 |
| 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, 2022 | 282* | 2022 |
| Autoregressive entity retrieval N De Cao, G Izacard, S Riedel, F Petroni International Conference on Learning Representations, 2020 | 179 | 2020 |
| Distilling Knowledge from Reader to Retriever for Question Answering G Izacard, E Grave International Conference on Learning Representations, 2021 | 89 | 2021 |
| Unsupervised dense information retrieval with contrastive learning G Izacard, M Caron, L Hosseini, S Riedel, P Bojanowski, A Joulin, ... Transactions on Machine Learning Research, 2022 | 80* | 2022 |
| 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 | 69 | 2021 |
| Neurips 2020 efficientqa competition: Systems, analyses and lessons learned S Min, J Boyd-Graber, C Alberti, D Chen, E Choi, M Collins, K Guu, ... NeurIPS 2020 Competition and Demonstration Track, 86-111, 2021 | 50 | 2021 |
| Atlas: Few-shot learning with retrieval augmented language models G Izacard, P Lewis, M Lomeli, L Hosseini, F Petroni, T Schick, ... arXiv preprint arXiv 2208, 2022 | 39* | 2022 |
| Data-driven estimation of sinusoid frequencies G Izacard, S Mohan, C Fernandez-Granda Advances in Neural Information Processing Systems 32, 2019 | 31 | 2019 |
| A memory efficient baseline for open domain question answering G Izacard, F Petroni, L Hosseini, N De Cao, S Riedel, E Grave arXiv preprint arXiv:2012.15156, 2020 | 28 | 2020 |
| A learning-based framework for line-spectra super-resolution G Izacard, B Bernstein, C Fernandez-Granda ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 28 | 2019 |
| A new analysis method for evolutionary optimization of dynamic and noisy objective functions R Dang-Nhu, T Dardinier, B Doerr, G Izacard, D Nogneng Proceedings of the Genetic and Evolutionary Computation Conference, 1467-1474, 2018 | 25 | 2018 |
| The Web Is Your Oyster--Knowledge-Intensive NLP against a Very Large Web Corpus A Piktus, F Petroni, V Karpukhin, D Okhonko, S Broscheit, G Izacard, ... arXiv preprint arXiv:2112.09924, 2021 | 16 | 2021 |
| PEER: A Collaborative Language Model T Schick, J Dwivedi-Yu, Z Jiang, F Petroni, P Lewis, G Izacard, Q You, ... arXiv preprint arXiv:2208.11663, 2022 | 13 | 2022 |
| Task-aware retrieval with instructions A Asai, T Schick, P Lewis, X Chen, G Izacard, S Riedel, H Hajishirzi, ... arXiv preprint arXiv:2211.09260, 2022 | 7 | 2022 |
| 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 | 6 | 2023 |
| Improving Wikipedia Verifiability with AI F Petroni, S Broscheit, A Piktus, P Lewis, G Izacard, L Hosseini, ... arXiv preprint arXiv:2207.06220, 2022 | 2 | 2022 |
| Lossless Data Compression with Transformer G Izacard, A Joulin, E Grave | 1 | |
| EditEval: An Instruction-Based Benchmark for Text Improvements J Dwivedi-Yu, T Schick, Z Jiang, M Lomeli, P Lewis, G Izacard, E Grave, ... arXiv preprint arXiv:2209.13331, 2022 | | 2022 |
Edouard GraveResearch Scientist, FacebookVerified email at fb.com
