Papers with cross-sentence ordering

1 papers
Discourse-Aware Neural Rewards for Coherent Text Generation (N18-1)

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Challenge: Existing approaches to train text generation models using cross-entropy loss do not always correlate well with achieving high scores on commonly used evaluation measures.
Approach: They propose to use discourse-aware rewards to model cross-sentence ordering to approximate desired discourse structure to train a model of long, coherent text.
Outcome: The proposed model produces more coherent and less repetitive text than models trained with cross-entropy or with commonly used scores as rewards.

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