Michael Auli
Michael Auli
Facebook AI Research
Verified email at fb.com
Title
Cited by
Cited by
Year
Convolutional sequence to sequence learning
J Gehring, M Auli, D Grangier, D Yarats, YN Dauphin
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
12302017
Sequence level training with recurrent neural networks
MA Ranzato, S Chopra, M Auli, W Zaremba
arXiv preprint arXiv:1511.06732, 2015
6802015
Language modeling with gated convolutional networks
YN Dauphin, A Fan, M Auli, D Grangier
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
6252017
A neural network approach to context-sensitive generation of conversational responses
A Sordoni, M Galley, M Auli, C Brockett, Y Ji, M Mitchell, JY Nie, J Gao, ...
arXiv preprint arXiv:1506.06714, 2015
5662015
Abstractive sentence summarization with attentive recurrent neural networks
S Chopra, M Auli, AM Rush
Proceedings of the 2016 Conference of the North American Chapter of the …, 2016
4162016
Joint language and translation modeling with recurrent neural networks
M Auli, M Galley, C Quirk, G Zweig
2392013
A convolutional encoder model for neural machine translation
J Gehring, M Auli, D Grangier, YN Dauphin
arXiv preprint arXiv:1611.02344, 2016
1842016
Understanding back-translation at scale
S Edunov, M Ott, M Auli, D Grangier
arXiv preprint arXiv:1808.09381, 2018
1242018
Neural text generation from structured data with application to the biography domain
R Lebret, D Grangier, M Auli
arXiv preprint arXiv:1603.07771, 2016
1192016
fairseq: A fast, extensible toolkit for sequence modeling
M Ott, S Edunov, A Baevski, A Fan, S Gross, N Ng, D Grangier, M Auli
arXiv preprint arXiv:1904.01038, 2019
1062019
Scaling neural machine translation
M Ott, S Edunov, D Grangier, M Auli
arXiv preprint arXiv:1806.00187, 2018
1032018
Strategies for training large vocabulary neural language models
W Chen, D Grangier, M Auli
arXiv preprint arXiv:1512.04906, 2015
1032015
deltaBLEU: A discriminative metric for generation tasks with intrinsically diverse targets
M Galley, C Brockett, A Sordoni, Y Ji, M Auli, C Quirk, M Mitchell, J Gao, ...
arXiv preprint arXiv:1506.06863, 2015
982015
Pay less attention with lightweight and dynamic convolutions
F Wu, A Fan, A Baevski, YN Dauphin, M Auli
arXiv preprint arXiv:1901.10430, 2019
752019
Classical structured prediction losses for sequence to sequence learning
S Edunov, M Ott, M Auli, D Grangier, MA Ranzato
arXiv preprint arXiv:1711.04956, 2017
602017
Controllable abstractive summarization
A Fan, D Grangier, M Auli
arXiv preprint arXiv:1711.05217, 2017
572017
Adaptive input representations for neural language modeling
A Baevski, M Auli
arXiv preprint arXiv:1809.10853, 2018
542018
CCG supertagging with a recurrent neural network
W Xu, M Auli, S Clark
Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015
532015
A comparison of loopy belief propagation and dual decomposition for integrated CCG supertagging and parsing
M Auli, A Lopez
Proceedings of the 49th Annual Meeting of the Association for Computational …, 2011
522011
3D human pose estimation in video with temporal convolutions and semi-supervised training
D Pavllo, C Feichtenhofer, D Grangier, M Auli
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
512019
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