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John Wieting
John Wieting
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Verified email at ttic.edu
Title
Cited by
Cited by
Year
Towards universal paraphrastic sentence embeddings
J Wieting, M Bansal, K Gimpel, K Livescu
arXiv preprint arXiv:1511.08198, 2015
6232015
Towards universal paraphrastic sentence embeddings
J Wieting, M Bansal, K Gimpel, K Livescu
arXiv preprint arXiv:1511.08198, 2015
6232015
Adversarial example generation with syntactically controlled paraphrase networks
M Iyyer, J Wieting, K Gimpel, L Zettlemoyer
arXiv preprint arXiv:1804.06059, 2018
4922018
From paraphrase database to compositional paraphrase model and back
J Wieting, M Bansal, K Gimpel, K Livescu
Transactions of the Association for Computational Linguistics 3, 345-358, 2015
2972015
From paraphrase database to compositional paraphrase model and back
J Wieting, M Bansal, K Gimpel, K Livescu
Transactions of the Association for Computational Linguistics 3, 345-358, 2015
2972015
ParaNMT-50M: Pushing the limits of paraphrastic sentence embeddings with millions of machine translations
J Wieting, K Gimpel
arXiv preprint arXiv:1711.05732, 2017
2452017
Charagram: Embedding words and sentences via character n-grams
J Wieting, M Bansal, K Gimpel, K Livescu
arXiv preprint arXiv:1607.02789, 2016
2272016
Reformulating unsupervised style transfer as paraphrase generation
K Krishna, J Wieting, M Iyyer
arXiv preprint arXiv:2010.05700, 2020
1132020
No training required: Exploring random encoders for sentence classification
J Wieting, D Kiela
arXiv preprint arXiv:1901.10444, 2019
1042019
compare-mt: A tool for holistic comparison of language generation systems
G Neubig, ZY Dou, J Hu, P Michel, D Pruthi, X Wang, J Wieting
arXiv preprint arXiv:1903.07926, 2019
952019
Learning paraphrastic sentence embeddings from back-translated bitext
J Wieting, J Mallinson, K Gimpel
arXiv preprint arXiv:1706.01847, 2017
932017
Revisiting recurrent networks for paraphrastic sentence embeddings
J Wieting, K Gimpel
arXiv preprint arXiv:1705.00364, 2017
932017
Beyond BLEU: training neural machine translation with semantic similarity
J Wieting, T Berg-Kirkpatrick, K Gimpel, G Neubig
arXiv preprint arXiv:1909.06694, 2019
772019
Canine: Pre-training an efficient tokenization-free encoder for language representation
JH Clark, D Garrette, I Turc, J Wieting
Transactions of the Association for Computational Linguistics 10, 73-91, 2022
632022
UMD-TTIC-UW at SemEval-2016 Task 1: Attention-Based Multi-Perspective Convolutional Neural Networks for Textual Similarity Measurement
H He, J Wieting, K Gimpel, J Rao, J Lin
342016
Simple and effective paraphrastic similarity from parallel translations
J Wieting, K Gimpel, G Neubig, T Berg-Kirkpatrick
arXiv preprint arXiv:1909.13872, 2019
322019
Pushing the limits of paraphrastic sentence embeddings with millions of machine translations
J Wieting, K Gimpel
arXiv preprint arXiv:1711.05732, 2017
282017
On learning text style transfer with direct rewards
Y Liu, G Neubig, J Wieting
arXiv preprint arXiv:2010.12771, 2020
202020
Improving candidate generation for low-resource cross-lingual entity linking
S Zhou, S Rijhwani, J Wieting, J Carbonell, G Neubig
Transactions of the Association for Computational Linguistics 8, 109-124, 2020
202020
Cogcompnlp: Your swiss army knife for nlp
D Khashabi, M Sammons, B Zhou, T Redman, C Christodoulopoulos, ...
Proceedings of the Eleventh International Conference on Language Resources …, 2018
192018
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