| Exploring the limits of transfer learning with a unified text-to-text transformer C Raffel, N Shazeer, A Roberts, K Lee, S Narang, M Matena, Y Zhou, W Li, ... Journal of Machine Learning Research, 2019 | 16669 | 2019 |
| Get To The Point: Summarization with Pointer-Generator Networks A See, PJ Liu, CD Manning ACL 2017, 2017 | 3509 | 2017 |
| Scalable and accurate deep learning with electronic health records A Rajkomar, E Oren, K Chen, AM Dai, N Hajaj, M Hardt, PJ Liu, X Liu, ... NPJ digital medicine 1 (1), 1-10, 2018 | 2177 | 2018 |
| Pegasus: Pre-training with extracted gap-sentences for abstractive summarization J Zhang, Y Zhao, M Saleh, PJ Liu ICML 2020, 2019 | 1997 | 2019 |
| Generating Wikipedia by Summarizing Long Sequences PJ Liu, M Saleh, E Pot, G Ben, R Sepassi, L Kaiser, N Shazeer ICLR 2018, 2018 | 950 | 2018 |
| Likelihood ratios for out-of-distribution detection J Ren, PJ Liu, E Fertig, J Snoek, R Poplin, M Depristo, J Dillon, ... Advances in neural information processing systems 32, 2019 | 718 | 2019 |
| Unsupervised Pretraining for Sequence to Sequence Learning P Ramachandran, PJ Liu, QV Le EMNLP 2017, 2016 | 348 | 2016 |
| Online and Linear-Time Attention by Enforcing Monotonic Alignments C Raffel, T Luong, PJ Liu, RJ Weiss, D Eck ICML 2017, 2017 | 311 | 2017 |
| Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs WJ Murdoch, PJ Liu, B Yu ICLR 2018, 2018 | 250 | 2018 |
| MeanSum: a neural model for unsupervised multi-document abstractive summarization E Chu, P Liu International Conference on Machine Learning, 1223-1232, 2019 | 247 | 2019 |
| Assessing The Factual Accuracy of Generated Text B Goodrich, V Rao, M Saleh, PJ Liu KDD 2019, 2019 | 200 | 2019 |
| Slic-hf: Sequence likelihood calibration with human feedback Y Zhao, R Joshi, T Liu, M Khalman, M Saleh, PJ Liu arXiv preprint arXiv:2305.10425, 2023 | 128 | 2023 |
| Calibrating sequence likelihood improves conditional language generation Y Zhao, M Khalman, R Joshi, S Narayan, M Saleh, PJ Liu The eleventh international conference on learning representations, 2022 | 87 | 2022 |
| Statistical rejection sampling improves preference optimization T Liu, Y Zhao, R Joshi, M Khalman, M Saleh, PJ Liu, J Liu arXiv preprint arXiv:2309.06657, 2023 | 81 | 2023 |
| Exploring the limits of transfer learning with a unified text-to-text transformer. arXiv C Raffel, N Shazeer, A Roberts, K Lee, S Narang, M Matena, Y Zhou, W Li, ... arXiv preprint arXiv:1910.10683, 2019 | 78 | 2019 |
| Out-of-distribution detection and selective generation for conditional language models J Ren, J Luo, Y Zhao, K Krishna, M Saleh, B Lakshminarayanan, PJ Liu The Eleventh International Conference on Learning Representations, 2022 | 46 | 2022 |
| Exploring the limits of transfer learning with a unified text-to-text transformer A Roberts, C Raffel, K Lee, M Matena, N Shazeer, PJ Liu, S Narang, W Li, ... Google, Tech. Rep., 2019 | 44 | 2019 |
| Investigating efficiently extending transformers for long input summarization J Phang, Y Zhao, PJ Liu EMNLP 2023, 2022 | 43 | 2022 |
| T5: Exploring the limits of transfer learning with a unified text-to-text transformer C Raffel, N Shazeer, A Roberts, K Lee, S Narang, M Matena, Y Zhou, W Li, ... Journal of Machine Learning Research 21, 1-67, 2020 | 42 | 2020 |
| Beyond human data: Scaling self-training for problem-solving with language models A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, PJ Liu, J Harrison, ... arXiv preprint arXiv:2312.06585, 2023 | 35 | 2023 |
Noam ShazeerCharacter.aiVerified email at character.ai
