| BLOOM: A 176B-Parameter Open-Access Multilingual Language Model TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... arXiv preprint arXiv:2211.05100, 2022 | 1801 | 2022 |
| The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data Only G Penedo, Q Malartic, D Hesslow, R Cojocaru, H Alobeidli, A Cappelli, ... Thirty-seventh Conference on Neural Information Processing Systems Datasets …, 2023 | 863* | 2023 |
| The Falcon Series of Open Language Models E Almazrouei, H Alobeidli, A Alshamsi, A Cappelli, R Cojocaru, M Debbah, ... arXiv preprint arXiv:2311.16867, 2023 | 732* | 2023 |
| What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization? T Wang, A Roberts, D Hesslow, T Le Scao, HW Chung, I Beltagy, ... International Conference on Machine Learning, 22964-22984, 2022 | 183 | 2022 |
| What Language Model to Train if You Have One Million GPU Hours? TL Scao, T Wang, D Hesslow, L Saulnier, S Bekman, MS Bari, ... arXiv preprint arXiv:2210.15424, 2022 | 121 | 2022 |
| Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures J Launay, I Poli, F Boniface, F Krzakala Advances in Neural Information Processing Systems 33, 2020 | 88 | 2020 |
| Principled Training of Neural Networks with Direct Feedback Alignment J Launay, I Poli, F Krzakala arXiv preprint arXiv:1906.04554, 2019 | 42 | 2019 |
| A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language Model I Lakim, E Almazrouei, I Abualhaol, M Debbah, J Launay Proceedings of BigScience Episode\# 5--Workshop on Challenges & Perspectives …, 2022 | 21 | 2022 |
| Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment J Launay, I Poli, K Müller, G Pariente, I Carron, L Daudet, F Krzakala, ... arXiv preprint arXiv:2012.06373, 2020 | 21 | 2020 |
| AlGhafa Evaluation Benchmark for Arabic Language Models E Almazrouei, R Cojocaru, M Baldo, Q Malartic, H Alobeidli, D Mazzotta, ... Proceedings of ArabicNLP 2023, 244-275, 2023 | 14 | 2023 |
| Adversarial robustness by design through analog computing and synthetic gradients A Cappelli, R Ohana, J Launay, L Meunier, I Poli, F Krzakala ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 13 | 2022 |
| Photonic differential privacy with direct feedback alignment R Ohana, H Medina, J Launay, A Cappelli, I Poli, L Ralaivola, ... Advances in Neural Information Processing Systems 34, 22010-22020, 2021 | 13 | 2021 |
| PAGnol: An extra-large French generative model J Launay, E Tommasone, B Pannier, F Boniface, A Chatelain, A Cappelli, ... Proceedings of the Thirteenth Language Resources and Evaluation Conference …, 2022 | 11 | 2022 |
| LightOn Optical Processing Unit: Scaling-up AI and HPC with a Non von Neumann co-processor C Brossollet, A Cappelli, I Carron, C Chaintoutis, A Chatelain, L Daudet, ... arXiv preprint arXiv:2107.11814, 2021 | 11 | 2021 |
| Method and system for machine learning using optical data I Poli, J Launay, K Müller, G Pariente, I Carron, L Daudet US Patent 11,137,289, 2021 | 8 | 2021 |
| Is the Number of Trainable Parameters All That Actually Matters? A Chatelain, A Djeghri, D Hesslow, J Launay I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 27-32, 2022 | 7 | 2022 |
| ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients A Cappelli, R Ohana, J Launay, L Meunier, I Poli ICML 2021 Workshop on Adversarial Machine Learning, 2021 | 7 | 2021 |
| Light-in-the-loop: using a photonics co-processor for scalable training of neural networks J Launay, I Poli, K Müller, I Carron, L Daudet, F Krzakala, S Gigan arXiv preprint arXiv:2006.01475, 2020 | 7 | 2020 |
| Scaling Laws Beyond Backpropagation MJ Filipovich, A Cappelli, D Hesslow, J Launay arXiv preprint arXiv:2210.14593, 2022 | 3 | 2022 |
| Analysis of factors affecting the performance of BIPV panels J Launay, EWM Lee, R Bennacer, RKK Yuen The European Physical Journal Applied Physics 84 (1), 10902, 2018 | 3 | 2018 |