Multi-Reward Reinforced Summarization with Saliency and Entailment (NAACL-HTL 2018)

arxiv.org

The authors propose a new summarization model that uses RL with two new reward functions:
  1. ROUGE-Sal: modifies ROUGE metric by up-weighting salient phrases detected via a keyphrase classifier;
  2. Entail: gives high reward scores to logically-entailed summaries judged via an entailment classifier.

They combine the rewards via a novel multi-reward optimization, where rewards are updated in alternate mini-batches and achieve state-of-the-art on CNN/Daily mail datasets.

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