# Learning To Split and Rephrase From Wikipedia Edit History

arXiv: https://arxiv.org/abs/1808.09468 · HTML: https://mlsanity.com/paper/1808.09468/

## Key facts

- Cited by 38 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Aug 2018.

## Built on by (most cited first, 30 of 38)

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- [Bridging Continuous and Discrete Spaces: Interpretable Sentence Representation Learning via Compositional Operations](https://mlsanity.com/paper/2305.14599/) (2023)
- [Split and Rephrase with Large Language Models](https://mlsanity.com/paper/2312.11075/) (2023)
- [Beyond Output Matching: Bidirectional Alignment for Enhanced In-Context Learning](https://mlsanity.com/paper/2312.17055/) (2023)
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- [Text Simplification for Comprehension-based Question-Answering](https://mlsanity.com/paper/2109.13984/) (2021)
- [Claim Optimization in Computational Argumentation](https://mlsanity.com/paper/2212.08913/) (2022)
- [With Measured Words: Simple Sentence Selection for Black-Box Optimization of Sentence Compression Algorithms](https://mlsanity.com/paper/2101.10096/) (2021)
- [Mitigating Data Scarcity for Large Language Models](https://mlsanity.com/paper/2302.01806/) (2023)
- [WikiSplit++: Easy Data Refinement for Split and Rephrase](https://mlsanity.com/paper/2404.09002/) (2024)

## Abstract (arXiv)

Split and rephrase is the task of breaking down a sentence into shorter ones that together convey the same meaning. We extract a rich new dataset for this task by mining Wikipedia's edit history: WikiSplit contains one million naturally occurring sentence rewrites, providing sixty times more distinct split examples and a ninety times larger vocabulary than the WebSplit corpus introduced by Narayan et al. (2017) as a benchmark for this task. Incorporating WikiSplit as training data produces a model with qualitatively better predictions that score 32 BLEU points above the prior best result on the WebSplit benchmark.