yixinL7/PageSum

EMNLP 2022: Leveraging Locality in Abstractive Text Summarization

23
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Experimental

This project helps researchers, analysts, or anyone dealing with lengthy documents to condense them into shorter, coherent summaries. It takes long-form text, such as scientific papers, news articles, or government reports, and outputs a concise abstract that captures the main points. This is useful for individuals who need to quickly grasp the essence of extensive content without reading every detail.

No commits in the last 6 months.

Use this if you need to automatically generate high-quality, abstractive summaries from very long documents like research papers, detailed reports, or multi-source news articles.

Not ideal if you need keyword extraction, extractive summaries (where sentences are directly copied from the original text), or summaries for very short texts.

academic-research news-analysis report-digestion information-synthesis text-understanding
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 9 / 25

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Stars

18

Forks

2

Language

Python

License

Last pushed

Oct 21, 2024

Commits (30d)

0

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