CNsum:Automatic Summarization for Chinese News Text
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Abstract (arXiv)
Obtaining valuable information from massive data efficiently has become our research goal in the era of Big Data. Text summarization technology has been continuously developed to meet this demand. Recent work has also shown that transformer-based pre-trained language models have achieved great success on various tasks in Natural Language Processing (NLP). Aiming at the problem of Chinese news text summary generation and the application of Transformer structure on Chinese, this paper proposes a Chinese news text summarization model (CNsum) based on Transformer structure, and tests it on Chinese datasets such as THUCNews. The results of the conducted experiments show that CNsum achieves better ROUGE score than the baseline models, which verifies the outperformance of the model.
Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 10 of its 27 references that are in the map. First posted on arXiv 27 Feb 2025.
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References · 10
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