MCTS: A Multi-Reference Chinese Text Simplification Dataset
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Abstract (arXiv)
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/.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 24 of its 42 references that are in the map. First posted on arXiv 5 Jun 2023.
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References · 24
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12 more
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