Papers with latent variable extractive model

1 papers
Neural Latent Extractive Document Summarization (D18-1)

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Challenge: Existing summarization paradigms focus on extractive summarizing based on sentence level labels .
Approach: They propose a latent variable extractive model where sentences are viewed as latent variables and sentences with activated variables are used to infer gold summaries.
Outcome: The proposed model outperforms a strong extractive baseline trained on rule-based labels and performs competitively with several recent models.

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