| Deep learning for symbolic mathematics G Lample, F Charton International Conference on Learning Representations (ICLR) 2020, 2019 | 573 | 2019 |
| End-to-end symbolic regression with transformers PA Kamienny, S d'Ascoli, G Lample, F Charton Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS) 2022, 2022 | 195 | 2022 |
| Leveraging automated unit tests for unsupervised code translation B Roziere, JM Zhang, F Charton, M Harman, G Synnaeve, G Lample International Conference on Learning Representations (ICLR) 2022, 2021 | 127 | 2021 |
| Deep symbolic regression for recurrence prediction S d’Ascoli, PA Kamienny, G Lample, F Charton International Conference on Machine Learning, ICML, 2022, 4520-4536, 2022 | 82* | 2022 |
| Code translation with compiler representations M Szafraniec, B Roziere, HLF Charton, P Labatut, G Synnaeve International conference on learning representations (ICLR) 2023, 2022 | 79 | 2022 |
| Linear algebra with transformers F Charton Transactions on Machine Learning Research (TMLR) October 2022, 2021 | 72 | 2021 |
| A tale of tails: Model collapse as a change of scaling laws E Dohmatob, Y Feng, P Yang, F Charton, J Kempe arXiv preprint arXiv:2402.07043, 2024 | 62 | 2024 |
| Learning advanced mathematical computations from examples F Charton, A Hayat, G Lample International Conference on Learning Representations (ICLR) 2021, 2020 | 43* | 2020 |
| SALSA: Attacking Lattice Cryptography with Transformers E Wenger, M Chen, F Charton, K Lauter Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS) 2022, 2022 | 42 | 2022 |
| Length generalization in arithmetic transformers S Jelassi, S d'Ascoli, C Domingo-Enrich, Y Wu, Y Li, F Charton arXiv preprint arXiv:2306.15400, 2023 | 37 | 2023 |
| Learning the greatest common divisor: explaining transformer predictions F Charton arXiv preprint arXiv:2308.15594, 2023 | 24* | 2023 |
| Back-to-back regression: Disentangling the influence of correlated factors from multivariate observations JR King, F Charton, D Lopez-Paz, M Oquab NeuroImage 220, 117028, 2020 | 22* | 2020 |
| Beyond model collapse: Scaling up with synthesized data requires reinforcement Y Feng, E Dohmatob, P Yang, F Charton, J Kempe ICML 2024 Workshop on Theoretical Foundations of Foundation Models, 2024 | 21* | 2024 |
| Transforming the bootstrap: using transformers to compute scattering amplitudes in planar super Yang–Mills theory T Cai, GW Merz, F Charton, N Nolte, M Wilhelm, K Cranmer, LJ Dixon Machine Learning: Science and Technology 5 (3), 035073, 2024 | 17 | 2024 |
| What is my math transformer doing?--Three results on interpretability and generalization F Charton The 2nd Workshop on Mathematical Reasoning and AI at NeurIPS'22, 2022 | 17 | 2022 |
| SALSA VERDE: a machine learning attack on LWE with sparse small secrets CY Li, E Wenger, Z Allen-Zhu, F Charton, KE Lauter Thirty-seventh Conference on Neural Information Processing Systems, 2024, 2023 | 15 | 2023 |
| Global lyapunov functions: a long-standing open problem in mathematics, with symbolic transformers A Alfarano, F Charton, A Hayat Advances in Neural Information Processing Systems 37, 93643-93670, 2024 | 14* | 2024 |
| SALSA PICANTE: a machine learning attack on LWE with binary secrets C Li, J Sotáková, E Wenger, M Malhou, E Garcelon, F Charton, K Lauter The thirtieth ACM Conference on Computer and Communications Security (CCS) 2023, 2023 | 13 | 2023 |
| PatternBoost: Constructions in mathematics with a little help from AI F Charton, JS Ellenberg, AZ Wagner, G Williamson arXiv preprint arXiv:2411.00566, 2024 | 9 | 2024 |
| Iteration head: A mechanistic study of chain-of-thought V Cabannes, C Arnal, W Bouaziz, X Yang, F Charton, J Kempe Advances in Neural Information Processing Systems 37, 109101-109122, 2024 | 7 | 2024 |
Guillaume LampleMistral AIVerified email at mistral.ai
