Pablo Rivas


2019

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Modeling Five Sentence Quality Representations by Finding Latent Spaces Produced with Deep Long Short-Memory Models
Pablo Rivas
Proceedings of the 2019 Workshop on Widening NLP

We present a study in which we train neural models that approximate rules that assess the quality of English sentences. We modeled five rules using deep LSTMs trained over a dataset of sentences whose quality is evaluated under such rules. Preliminary results suggest the neural architecture can model such rules to high accuracy.
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