Jointly Measuring Diversity and Quality in Text Generation Models

Published: Jan 1, 2019
Abstract
Text generation is an important Natural Language Processing task with various applications. Although several metrics have already been introduced to evaluate the text generation methods, each of them has its own shortcomings. The most widely used metrics such as BLEU only consider the quality of generated sentences and neglecting their diversity. For example, repeatedly generation of only one high quality sentence would result in a high BLEU...
Paper Details
Title
Jointly Measuring Diversity and Quality in Text Generation Models
Published Date
Jan 1, 2019
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