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Generation-Distillation for Efficient Natural Language Understanding in Low-Data Settings
Luke Melas-Kyriazi
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George Han
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Celine Liang
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Paper Details:
Month: November
Year: 2019
Location: Hong Kong, China
Venue:
EMNLP |
WS |
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https://doi.org/10.18653/v1/P17
https://github.com/
Field Of Study
Linguistic Trends
Embeddings
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Language Understanding
Question Answering
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Generative Model
Representation Learning
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