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Alexander M. Rush
Alexander M. Rush
Associate Professor, Cornell University
Verified email at seas.harvard.edu - Homepage
Title
Cited by
Cited by
Year
Transformers: State-of-the-art natural language processing
T Wolf, L Debut, V Sanh, J Chaumond, C Delangue, A Moi, P Cistac, ...
Proceedings of the 2020 conference on empirical methods in natural language†…, 2020
5248*2020
A neural attention model for abstractive sentence summarization
AM Rush, S Chopra, J Weston
arXiv preprint arXiv:1509.00685, 2015
31732015
Opennmt: Open-source toolkit for neural machine translation
G Klein, Y Kim, Y Deng, J Senellart, AM Rush
arXiv preprint arXiv:1701.02810, 2017
20692017
Character-aware neural language models
Y Kim, Y Jernite, D Sontag, A Rush
Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016
20372016
Towards ai-complete question answering: A set of prerequisite toy tasks
J Weston, A Bordes, S Chopra, AM Rush, B Van MerriŽnboer, A Joulin, ...
arXiv preprint arXiv:1502.05698, 2015
11642015
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
10572016
Sequence-level knowledge distillation
Y Kim, AM Rush
arXiv preprint arXiv:1606.07947, 2016
9092016
Bottom-up abstractive summarization
S Gehrmann, Y Deng, AM Rush
arXiv preprint arXiv:1808.10792, 2018
7312018
Multitask prompted training enables zero-shot task generalization
V Sanh, A Webson, C Raffel, SH Bach, L Sutawika, Z Alyafeai, A Chaffin, ...
arXiv preprint arXiv:2110.08207, 2021
6722021
Sequence-to-sequence learning as beam-search optimization
S Wiseman, AM Rush
arXiv preprint arXiv:1606.02960, 2016
6012016
Challenges in data-to-document generation
S Wiseman, SM Shieber, AM Rush
arXiv preprint arXiv:1707.08052, 2017
5522017
Structured attention networks
Y Kim, C Denton, L Hoang, AM Rush
arXiv preprint arXiv:1702.00887, 2017
5152017
Bloom: A 176b-parameter open-access multilingual language model
TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagnť, ...
arXiv preprint arXiv:2211.05100, 2022
4722022
Lstmvis: A tool for visual analysis of hidden state dynamics in recurrent neural networks
H Strobelt, S Gehrmann, H Pfister, AM Rush
IEEE transactions on visualization and computer graphics 24 (1), 667-676, 2017
4552017
Adversarially regularized autoencoders
J Zhao, Y Kim, K Zhang, A Rush, Y LeCun
International conference on machine learning, 5902-5911, 2018
3062018
Image-to-markup generation with coarse-to-fine attention
Y Deng, A Kanervisto, J Ling, AM Rush
International Conference on Machine Learning, 980-989, 2017
269*2017
Semi-amortized variational autoencoders
Y Kim, S Wiseman, A Miller, D Sontag, A Rush
International Conference on Machine Learning, 2678-2687, 2018
2572018
Movement pruning: Adaptive sparsity by fine-tuning
V Sanh, T Wolf, A Rush
Advances in Neural Information Processing Systems 33, 20378-20389, 2020
2482020
Commonsense knowledge mining from pretrained models
J Davison, J Feldman, AM Rush
Proceedings of the 2019 conference on empirical methods in natural language†…, 2019
2442019
Learning global features for coreference resolution
S Wiseman, AM Rush, SM Shieber
arXiv preprint arXiv:1604.03035, 2016
2422016
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