Papers by Eric Crawford

1 papers
BanditSum: Extractive Summarization as a Contextual Bandit (D18-1)

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Challenge: Existing methods for extractive summarization are heuristically generated and require a set of binary labels to be selected.
Approach: They propose a method for training neural networks to perform single-document extractive summarization without heuristically-generated extractive labels.
Outcome: The proposed method achieves better ROUGE scores than the state-of-the-art methods and significantly fewer update steps than competing approaches.

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