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Distributed representations of sentences have become ubiquitous in natural language processing tasks.
Semeval-2012 task 6: A pilot on semantic textual similarity
E. Agirre, M. Diab, D. Cer, and A. Gonzalez-Agirre. 2012 · 2012
Earlier work this paper cites.
Sem 2013 shared task: Semantic textual similarity
E. Agirre, D. Cer, M. Diab, A. Gonzalez-Agirre, and W. Guo. 2013 · 2013
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Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean. 2013 · 2013
Earlier work this paper cites.
Semeval-2014 task 10: Multilingual semantic textual similarity
E. Agirre, C. Banea, C. Cardie, D. Cer, M. Diab, A. Gonzalez-Agirre, W. Guo, R. Mihalcea, G. Rigau, and J. Wiebe. 2014 · 2014
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Controlling recurrent neural networks by conceptors
H. Jaeger. 2014 · 2014
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Glove: Global vectors for word representation
J. Pennington, R. Socher, and C. D. Manning. 2014 · 2014
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Semeval-2015 task 2: Semantic textual similarity, English, Spanish and pilot on interpretability
E. Agirre, C. Banea, C. Cardie, D. Cer, M. Diab, A. Gonzalez-Agirre, W. Guo, I. Lopez-Gazpio, M. Maritxalar, R. Mihalcea, G. Rigaua, L. Uriaa, and J. Wiebeg. 2015 · 2015
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From paraphrase database to compositional paraphrase model and back
J. Wieting, M. Bansal, K. Gimpel, K. Livescu, and D. Roth. 2015 · 2015
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Convolutional neural network for paraphrase identification
W. Yin and H. Schütze. 2015 · 2015
Cited alongside, same era.
Semeval-2016 task 1: Semantic textual similarity, monolingual and cross-lingual evaluation
E. Agirre, C. Banea, D. Cer, M. Diab, A. Gonzalez-Agirre, R. Mihalcea, G. Rigau, and J. Wiebe. 2016 · 2016
Cited alongside, same era.
A simple but tough-to-beat baseline for sentence embeddings
S. Arora, Y. Liang, and T. Ma. 2017 · 2017
Cited alongside, same era.
Enriching word vectors with subword information
P. Bojanowski, E. Grave, A. Joulin, and T. Mikolov. 2017 · 2017
Cited alongside, same era.
Using conceptors to manage neural long-term memories for temporal patterns
H. Jaeger. 2017 · 2017
Cited alongside, same era.
Toward continual learning for conversational agents
S. Lee. 2017 · 2017
Cited alongside, same era.
Senteval: An evaluation toolkit for universal sentence representations
A. Conneau and D. Kiela. 2018 · 2018
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Overcoming catastrophic interference using conceptor-aided backpropagation
X. He and H. Jaeger. 2018 · 2018
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A la carte embedding: Cheap but effective induction of semantic feature vectors
M. Khodak, N. Saunshi, Y. Liang, T. Ma, B. Stewart, and S. Arora. 2018 · 2018
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The rapidly changing landscape of conversational agents
V. Mathur and A. Singh. 2018 · 2018
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Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features
M. Pagliardini, P. Gupta, and M. Jaggi. 2018 · 2018
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Continual learning through synaptic intelligence
F. Zenke, B. Poole, and S. Ganguli. 2017 · 2017
Cited alongside, same era.
D. Cer, Y. Yang, S. Kong, N. Hua, N. Limtiaco, R. John, N. Constant, M. Guajardo-Cespedes, S. Yuan, C. Tar, et al. 2018 · 2018
Cited alongside, same era.
Zero-training sentence embedding via orthogonal basis
Z. Yang, C. Zhu, and W. Chen. 2018 · 2018
Later among the works it cites.
Unsupervised post-processing of word vectors via conceptor negation
T. Liu, L. Ungar, and J. Sedoc. 2019 · 2019
Closest in time.
GLUE: A multi-task benchmark and analysis platform for natural language understanding
A. Wang, A. Singh, J. Michael, F. Hill, O. Levy, and S. R. Bowman. 2019 · 2019
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