Google's neural machine translation system: Bridging the gap between human and machine translation Y Wu, M Schuster, Z Chen, QV Le, M Norouzi, W Macherey, M Krikun, ... arXiv preprint arXiv:1609.08144, 2016 | 9145 | 2016 |
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 702 | 2024 |
The best of both worlds: Combining recent advances in neural machine translation MX Chen, O Firat, A Bapna, M Johnson, W Macherey, G Foster, L Jones, ... arXiv preprint arXiv:1804.09849, 2018 | 540 | 2018 |
Massively multilingual neural machine translation in the wild: Findings and challenges N Arivazhagan, A Bapna, O Firat, D Lepikhin, M Johnson, M Krikun, ... arXiv preprint arXiv:1907.05019, 2019 | 419 | 2019 |
Experts, errors, and context: A large-scale study of human evaluation for machine translation M Freitag, G Foster, D Grangier, V Ratnakar, Q Tan, W Macherey Transactions of the Association for Computational Linguistics 9, 1460-1474, 2021 | 348 | 2021 |
Robust neural machine translation with doubly adversarial inputs Y Cheng, L Jiang, W Macherey arXiv preprint arXiv:1906.02443, 2019 | 282 | 2019 |
Direct speech-to-speech translation with a sequence-to-sequence model Y Jia, RJ Weiss, F Biadsy, W Macherey, M Johnson, Z Chen, Y Wu arXiv preprint arXiv:1904.06037, 2019 | 245 | 2019 |
Lingvo: a modular and scalable framework for sequence-to-sequence modeling J Shen, P Nguyen, Y Wu, Z Chen, MX Chen, Y Jia, A Kannan, T Sainath, ... arXiv preprint arXiv:1902.08295, 2019 | 214 | 2019 |
Monotonic infinite lookback attention for simultaneous machine translation N Arivazhagan, C Cherry, W Macherey, CC Chiu, S Yavuz, R Pang, W Li, ... arXiv preprint arXiv:1906.05218, 2019 | 199 | 2019 |
Reinforced self-training (rest) for language modeling C Gulcehre, TL Paine, S Srinivasan, K Konyushkova, L Weerts, A Sharma, ... arXiv preprint arXiv:2308.08998, 2023 | 190 | 2023 |
Leveraging weakly supervised data to improve end-to-end speech-to-text translation Y Jia, M Johnson, W Macherey, RJ Weiss, Y Cao, CC Chiu, N Ari, ... ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 180 | 2019 |
Lattice Minimum Bayes-Risk decoding for statistical machine translation R Tromble, S Kumar, FJ Och, W Macherey Proceedings of the 2008 Conference on Empirical Methods in Natural Language …, 2008 | 166 | 2008 |
Comparison of discriminative training criteria and optimization methods for speech recognition R Schlüter, W Macherey, B Müller, H Ney Speech Communication 34 (3), 287-310, 2001 | 133 | 2001 |
Lattice-based minimum error rate training for statistical machine translation W Macherey, FJ Och, I Thayer, J Uszkoreit Proceedings of the 2008 Conference on Empirical Methods in Natural Language …, 2008 | 132 | 2008 |
Revisiting character-based neural machine translation with capacity and compression C Cherry, G Foster, A Bapna, O Firat, W Macherey arXiv preprint arXiv:1808.09943, 2018 | 125 | 2018 |
Advaug: Robust adversarial augmentation for neural machine translation Y Cheng, L Jiang, W Macherey, J Eisenstein arXiv preprint arXiv:2006.11834, 2020 | 117 | 2020 |
The missing ingredient in zero-shot neural machine translation N Arivazhagan, A Bapna, O Firat, R Aharoni, M Johnson, W Macherey arXiv preprint arXiv:1903.07091, 2019 | 114 | 2019 |
Investigations on error minimizing training criteria for discriminative training in automatic speech recognition. W Macherey, L Haferkamp, R Schlüter, H Ney Interspeech 2005, 2133-2136, 2005 | 105 | 2005 |
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Efficient minimum error rate training and minimum bayes-risk decoding for translation hypergraphs and lattices S Kumar, W Macherey, C Dyer, FJ Och Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL …, 2009 | 102 | 2009 |