MCTS: A Multi-Reference Chinese Text Simplification Dataset

Ruining Chong, Luming Lu, Liner Yang, Jinran Nie, Zhenghao Liu +4 more
6/5/2023
cs.CL

Official code: blcuicall/mcts (36 stars, last commit 2024-06-03).

Abstract

Text simplification aims to make the text easier to understand by applying rewriting transformations. There has been very little research on Chinese text simplification for a long time. The lack of generic evaluation data is an essential reason for this phenomenon. In this paper, we introduce MCTS, a multi-reference Chinese text simplification dataset. We describe the annotation process of the dataset and provide a detailed analysis. Furthermore, we evaluate the performance of several unsupervised methods and advanced large language models. We additionally provide Chinese text simplification parallel data that can be used for training, acquired by utilizing machine translation and English text simplification. We hope to build a basic understanding of Chinese text simplification through the foundational work and provide references for future research. All of the code and data are released at https://github.com/blcuicall/mcts/.

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Code and data of the paper "MCTS: A Multi-Reference Chinese Text Simplification Dataset".

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@article{chong2023mcts,
  title  = {MCTS: A Multi-Reference Chinese Text Simplification Dataset},
  author = {Ruining Chong and Luming Lu and Liner Yang and Jinran Nie and Zhenghao Liu and Shuo Wang and Shuhan Zhou and Yaoxin Li and Erhong Yang},
  year   = {2023},
  eprint = {2306.02796},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.02796v3}
}

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