Data Augmentation with Seq2Seq Models
Paraphrase sparsity is an issue that complicates the training process of question answering systems: syntactically diverse but semantically equivalent sentences can have significant disparities in predicted output probabilities. We propose a method for generating an augmented paraphrase corpus for t...
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Virginia Tech
2017
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| Online Access: | http://hdl.handle.net/10919/78315 |