Követés
Alexander M. Rush
Alexander M. Rush
Associate Professor, Cornell University
E-mail megerősítve itt: cornell.edu - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Transformers: State-of-the-Art Natural Language Processing
T Wolf
arXiv preprint arXiv:1910.03771, 2020
94172020
A neural attention model for abstractive sentence summarization
AM Rush
arXiv preprint arXiv:1509.00685, 2015
36232015
Opennmt: Open-source toolkit for neural machine translation
G Klein, Y Kim, Y Deng, J Senellart, AM Rush
arXiv preprint arXiv:1701.02810, 2017
23592017
Character-aware neural language models
Y Kim, Y Jernite, D Sontag, A Rush
Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016
22402016
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
17722021
Bloom: A 176b-parameter open-access multilingual language model
T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ...
17482023
Towards ai-complete question answering: A set of prerequisite toy tasks
J Weston, A Bordes, S Chopra, AM Rush, B Van Merriënboer, A Joulin, ...
arXiv preprint arXiv:1502.05698, 2015
13302015
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
12222016
Sequence-level knowledge distillation
Y Kim, AM Rush
arXiv preprint arXiv:1606.07947, 2016
11852016
Bottom-up abstractive summarization
S Gehrmann, Y Deng, AM Rush
arXiv preprint arXiv:1808.10792, 2018
8662018
Challenges in data-to-document generation
S Wiseman, SM Shieber, AM Rush
arXiv preprint arXiv:1707.08052, 2017
6832017
Sequence-to-sequence learning as beam-search optimization
S Wiseman, AM Rush
arXiv preprint arXiv:1606.02960, 2016
6832016
Structured attention networks
Y Kim, C Denton, L Hoang, AM Rush
arXiv preprint arXiv:1702.00887, 2017
6512017
Gltr: Statistical detection and visualization of generated text
S Gehrmann, H Strobelt, AM Rush
arXiv preprint arXiv:1906.04043, 2019
5802019
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
5672017
Movement pruning: Adaptive sparsity by fine-tuning
V Sanh, T Wolf, A Rush
Advances in neural information processing systems 33, 20378-20389, 2020
4912020
Zephyr: Direct distillation of lm alignment
L Tunstall, E Beeching, N Lambert, N Rajani, K Rasul, Y Belkada, ...
arXiv preprint arXiv:2310.16944, 2023
4842023
Parameter-efficient transfer learning with diff pruning
D Guo, AM Rush, Y Kim
arXiv preprint arXiv:2012.07463, 2020
4122020
Adversarially regularized autoencoders
J Zhao, Y Kim, K Zhang, A Rush, Y LeCun
International conference on machine learning, 5902-5911, 2018
3732018
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
361*2017
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Cikkek 1–20