| Palm: Scaling language modeling with pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... Journal of Machine Learning Research 24 (240), 1-113, 2023 | 5275 | 2023 |
| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023 | 2240 | 2023 |
| Gpipe: Efficient training of giant neural networks using pipeline parallelism Y Huang, Y Cheng, A Bapna, O Firat, D Chen, M Chen, HJ Lee, J Ngiam, ... Advances in neural information processing systems 32, 2019 | 1817 | 2019 |
| Palm 2 technical report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ... arXiv preprint arXiv:2305.10403, 2023 | 1489 | 2023 |
| Gshard: Scaling giant models with conditional computation and automatic sharding D Lepikhin, HJ Lee, Y Xu, D Chen, O Firat, Y Huang, M Krikun, N Shazeer, ... arXiv preprint arXiv:2006.16668, 2020 | 1027 | 2020 |
| Xtreme: A massively multilingual multi-task benchmark for evaluating cross-lingual generalisation J Hu, S Ruder, A Siddhant, G Neubig, O Firat, M Johnson International Conference on Machine Learning, 4411-4421, 2020 | 938 | 2020 |
| Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv e-prints, arXiv: 1605.02688, 2016 | 932 | 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 | 812 | 2024 |
| Multi-way, multilingual neural machine translation with a shared attention mechanism O Firat, K Cho, Y Bengio arXiv preprint arXiv:1601.01073, 2016 | 715 | 2016 |
| On using monolingual corpora in neural machine translation C Gulcehre, O Firat, K Xu, K Cho, L Barrault, HC Lin, F Bougares, ... arXiv preprint arXiv:1503.03535, 2015 | 661 | 2015 |
| Massively multilingual neural machine translation R Aharoni, M Johnson, O Firat arXiv preprint arXiv:1903.00089, 2019 | 605 | 2019 |
| Glam: Efficient scaling of language models with mixture-of-experts N Du, Y Huang, AM Dai, S Tong, D Lepikhin, Y Xu, M Krikun, Y Zhou, ... International Conference on Machine Learning, 5547-5569, 2022 | 576 | 2022 |
| 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 | 543 | 2018 |
| Simple, scalable adaptation for neural machine translation A Bapna, N Arivazhagan, O Firat arXiv preprint arXiv:1909.08478, 2019 | 469 | 2019 |
| Nematus: a toolkit for neural machine translation R Sennrich, O Firat, K Cho, A Birch, B Haddow, J Hitschler, ... arXiv preprint arXiv:1703.04357, 2017 | 454 | 2017 |
| 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 | 422 | 2019 |
| Zero-resource translation with multi-lingual neural machine translation O Firat, B Sankaran, Y Al-Onaizan, FTY Vural, K Cho arXiv preprint arXiv:1606.04164, 2016 | 285 | 2016 |
| Gemini: A family of highly capable multimodal models R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805 1, 2023 | 261 | 2023 |
| Theano: A Python framework for fast computation of mathematical expressions TTD Team, R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, ... arXiv preprint arXiv:1605.02688, 2016 | 219 | 2016 |
| 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 |
