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Recent Trends in Unsupervised Summarization

arXiv 2305.11231 ↗First posted 18 May 2023cs.CLcited by 0

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Abstract (arXiv)

Unsupervised summarization is a powerful technique that enables training summarizing models without requiring labeled datasets. This survey covers different recent techniques and models used for unsupervised summarization. We cover extractive, abstractive, and hybrid models and strategies used to achieve unsupervised summarization. While the main focus of this survey is on recent research, we also cover some of the important previous research. We additionally introduce a taxonomy, classifying different research based on their approach to unsupervised training. Finally, we discuss the current approaches and mention some datasets and evaluation methods.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 65 of its 99 references that are in the map. First posted on arXiv 18 May 2023.

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References · 65

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38 more
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