Browse State-of-the-Art › Unsupervised Sentence Compression
Unsupervised Sentence Compression
4 papers with code · 0 benchmarks · 0 datasets archive 2025-07-28
Producing a shorter sentence by removing redundant information, preserving the grammatically and the important content of the original sentence without supervision. (Source: nlpprogress.com)
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
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Datasets archive 2025-07-28
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Subtasks archive 2025-07-28
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Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
4 shown of 4 papers with code (4 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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17 May 2022 1 repository listedSentence compression reduces the length of text by removing non-essential content while preserving important facts and grammaticality.
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1 Jun 2019 1 repository listedThe proposed model does not require parallel text-summary pairs, achieving promising results in unsupervised sentence compression on benchmark datasets.
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7 Apr 2019 1 repository listedThe proposed model does not require parallel text-summary pairs, achieving promising results in unsupervised sentence compression on benchmark datasets.
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7 Sep 2018 1 repository listedIn sentence compression, the task of shortening sentences while retaining the original meaning, models tend to be trained on large corpora containing pairs of verbose and compressed sentences.
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