Papers with extractive and abstractive summarization systems

2 papers
DACSA: A large-scale Dataset for Automatic summarization of Catalan and Spanish newspaper Articles (2022.naacl-main)

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Challenge: a large corpus of documents is available for summarization tasks in English . supervised methods require adequate corpora for summarizing .
Approach: They describe a corpus of catalan and spanish newspapers that can be used to train summarization models for Catalan, Spanish and other languages.
Outcome: The proposed corpus can be used to train summarization models for Catalan and Spanish.
CoLo: A Contrastive Learning Based Re-ranking Framework for One-Stage Summarization (2022.coling-1)

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Challenge: Existing methods for extractive and abstractive summarization use token-level or sentence-level training objectives.
Approach: They propose a Contrastive Learning based re-ranking framework for one-stage summarization called CoLo.
Outcome: The proposed framework boosts extractive and abstractive results on CNN/DailyMail benchmarks while maintaining inference efficiency.

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