| Convolutional sequence to sequence learning J Gehring, M Auli, D Grangier, D Yarats, YN Dauphin International conference on machine learning, 1243-1252, 2017 | 4450 | 2017 |
| 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 | 1836 | 2023 |
| A convolutional encoder model for neural machine translation J Gehring, M Auli, D Grangier, YN Dauphin arXiv preprint arXiv:1611.02344, 2016 | 610 | 2016 |
| Extracting Deep Bottleneck Features Using Stacked Auto-Encoders J Gehring, Y Miao, F Metze, A Waibel Proceedings of the 2013 IEEE International Conference on Acoustics Speech …, 2013 | 393 | 2013 |
| Code llama: Open foundation models for code, 2023 B Rozière, J Gehring, F Gloeckle, S Sootla, I Gat, XE Tan, Y Adi, J Liu, ... URL https://arxiv. org/abs/2308.12950, 2023 | 63 | 2023 |
| Models of tone for tonal and non-tonal languages F Metze, ZAW Sheikh, A Waibel, J Gehring, K Kilgour, QB Nguyen 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 261-266, 2013 | 61 | 2013 |
| Stardata: A starcraft ai research dataset Z Lin, J Gehring, V Khalidov, G Synnaeve Proceedings of the AAAI Conference on Artificial Intelligence and …, 2017 | 52 | 2017 |
| Large language models for compiler optimization C Cummins, V Seeker, D Grubisic, M Elhoushi, Y Liang, B Roziere, ... arXiv preprint arXiv:2309.07062, 2023 | 51 | 2023 |
| Hierarchical skills for efficient exploration J Gehring, G Synnaeve, A Krause, N Usunier Advances in Neural Information Processing Systems 34, 11553-11564, 2021 | 48 | 2021 |
| Modular Combination of Deep Neural Networks for Acoustic Modeling J Gehring, W Lee, K Kilgour, I Lane, Y Miao, A Waibel Proc. Interspeech, 2013 | 42 | 2013 |
| Forward modeling for partial observation strategy games-a starcraft defogger G Synnaeve, Z Lin, J Gehring, D Gant, V Mella, V Khalidov, N Carion, ... Advances in Neural Information Processing Systems 31, 2018 | 34 | 2018 |
| Multilingual shifting deep bottleneck features for low-resource ASR QB Nguyen, J Gehring, M Müller, S Stüker, A Waibel 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 28 | 2014 |
| Meta large language model compiler: Foundation models of compiler optimization C Cummins, V Seeker, D Grubisic, B Roziere, J Gehring, G Synnaeve, ... arXiv preprint arXiv:2407.02524, 2024 | 24 | 2024 |
| Optimizing deep bottleneck feature extraction QB Nguyen, J Gehring, K Kilgour, A Waibel The 2013 RIVF International Conference on Computing & Communication …, 2013 | 19 | 2013 |
| The larger the better? improved llm code-generation via budget reallocation M Hassid, T Remez, J Gehring, R Schwartz, Y Adi arXiv preprint arXiv:2404.00725, 2024 | 18 | 2024 |
| DNN acoustic modeling with modular multi-lingual feature extraction networks J Gehring, QB Nguyen, F Metze, A Waibel 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 344-349, 2013 | 13 | 2013 |
| Segmentation of telephone speech based on speech and non-speech models M Heck, C Mohr, S Stüker, M Müller, K Kilgour, J Gehring, QB Nguyen, ... Speech and Computer: 15th International Conference, SPECOM 2013, Pilsen …, 2013 | 11 | 2013 |
| The 2013 KIT IWSLT Speech-to-Text Systems for German and English K Kilgour, C Mohr, M Heck, QB Nguyen, E Shin, I Tseyzer, J Gehring, ... Proceedings of the 10th International Workshop on Spoken Language …, 2013 | 9 | 2013 |
| Rlef: Grounding code llms in execution feedback with reinforcement learning J Gehring, K Zheng, J Copet, V Mella, Q Carbonneaux, T Cohen, ... arXiv preprint arXiv:2410.02089, 2024 | 8 | 2024 |
| High-level strategy selection under partial observability in starcraft: Brood war J Gehring, D Ju, V Mella, D Gant, N Usunier, G Synnaeve arXiv preprint arXiv:1811.08568, 2018 | 8 | 2018 |
Yann N. DauphinGoogle AIVerifierad e-postadress på dauphin.io