DS1 spectrogram: MCTS: A Multi-Reference Chinese Text Simplification Dataset

MCTS: A Multi-Reference Chinese Text Simplification Dataset

2306.02796

Authors

Ruining Chong,Liner Yang,Jinran Nie,Zhenghao Liu,Shuo Wang

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/.

Resources

Stay in the loop

Every AI paper that matters, free in your inbox daily.

Details

  • takara.ai
  • Custom AI and machine learning from the Frontier Research Team.
  • © 2026 takara.ai Ltd
  • Content is sourced from third-party publications.