Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning

Yacine Jernite; Samuel R. Bowman; David Sontag

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arXiv · 1705.00557

Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning

Yacine Jernite·Samuel R. Bowman·David Sontag

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Abstract

This work presents a novel objective function for the unsupervised training of neural network sentence encoders. It exploits signals from paragraph-level discourse coherence to train these models to understand text. Our objective is purely discriminative, allowing us to train models many times faster than was possible under prior methods, and it yields models which perform well in extrinsic evaluations.

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BibTeX RIS

Yacine Jernite, Samuel R. Bowman, David Sontag. 2017-04-23. Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning. https://arxiv.org/abs/1705.00557

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