| Roberta: A robustly optimized bert pretraining approach Y Liu, M Ott, N Goyal, J Du, M Joshi, D Chen, O Levy, M Lewis, ... arXiv preprint arXiv:1907.11692, 2019 | 28091* | 2019 |
| Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension M Lewis arXiv preprint arXiv:1910.13461, 2019 | 10748 | 2019 |
| Spanbert: Improving pre-training by representing and predicting spans M Joshi, D Chen, Y Liu, DS Weld, L Zettlemoyer, O Levy Transactions of the association for computational linguistics 8, 64-77, 2020 | 2184 | 2020 |
| Multilingual denoising pre-training for neural machine translation Y Liu, J Gu, N Goyal, X Li, S Edunov, M Ghazvininejad, M Lewis, ... arXiv preprint arXiv:2001.08210, 2020 | 1767 | 2020 |
| Chromatographic peak alignment using derivative dynamic time warping C Bork, K Ng, Y Liu, A Yee, M Pohlscheidt Biotechnology Progress 29 (2), 394-402, 2013 | 1627 | 2013 |
| Recipes for building an open-domain chatbot S Roller arXiv preprint arXiv:2004.13637, 2020 | 1067 | 2020 |
| Mask-predict: Parallel decoding of conditional masked language models M Ghazvininejad, O Levy, Y Liu, L Zettlemoyer arXiv preprint arXiv:1904.09324, 2019 | 578 | 2019 |
| Cloze-driven pretraining of self-attention networks A Baevski, S Edunov, Y Liu, L Zettlemoyer, M Auli arXiv preprint arXiv:1903.07785, 2019 | 273 | 2019 |
| Hierarchical learning for generation with long source sequences T Rohde, X Wu, Y Liu arXiv preprint arXiv:2104.07545, 2021 | 58 | 2021 |
| A robustly optimized bert pretraining approach L Yinhan, O Myle, G Naman, D Jingfei, J Mandar, C Danqi, L Omer, ... preprint, 2019 | 5 | 2019 |
