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Peter J. Liu
Peter J. Liu
Google Research, Brain Team, peterjliu.com
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
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
160212019
Get To The Point: Summarization with Pointer-Generator Networks
A See, PJ Liu, CD Manning
ACL 2017, 2017
34692017
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
21282018
Pegasus: Pre-training with extracted gap-sentences for abstractive summarization
J Zhang, Y Zhao, M Saleh, PJ Liu
ICML 2020, 2019
19452019
Generating Wikipedia by Summarizing Long Sequences
PJ Liu, M Saleh, E Pot, G Ben, R Sepassi, L Kaiser, N Shazeer
ICLR 2018, 2018
9342018
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
7052019
Unsupervised Pretraining for Sequence to Sequence Learning
P Ramachandran, PJ Liu, QV Le
EMNLP 2017, 2016
3432016
Online and Linear-Time Attention by Enforcing Monotonic Alignments
C Raffel, T Luong, PJ Liu, RJ Weiss, D Eck
ICML 2017, 2017
3082017
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs
WJ Murdoch, PJ Liu, B Yu
ICLR 2018, 2018
2462018
MeanSum: a neural model for unsupervised multi-document abstractive summarization
E Chu, P Liu
International Conference on Machine Learning, 1223-1232, 2019
2392019
Assessing The Factual Accuracy of Generated Text
B Goodrich, V Rao, M Saleh, PJ Liu
KDD 2019, 2019
1922019
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
1082023
System and method for predicting and summarizing medical events from electronic health records
A Mossin, A Rajkomar, E Oren, J Wilson, J Wexler, P Sundberg, A Dai, ...
US Patent 11,935,634, 2024
82*2024
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
802022
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
722019
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
662023
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
442019
Investigating efficiently extending transformers for long input summarization
J Phang, Y Zhao, PJ Liu
EMNLP 2023, 2022
422022
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
392022
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
352023
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