Publication: 20 Minuten: A Multi-task News Summarisation Dataset for German
20 Minuten: A Multi-task News Summarisation Dataset for German
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Kew, T., Kostrzewa, M., & Ebling, S. (2023). 20 Minuten: A Multi-task News Summarisation Dataset for German. Proceedings of the Swiss Text Analytics Conference, 1–13. https://aclanthology.org/2023.swisstext-1.1
Abstract
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Abstract
Automatic text summarisation (ATS) is a central task in natural language processing that aims to reduce a long document into a shorter, concise summary that conveys its key points. Extractive approaches to ATS, which identify and copy the most important sentences or phrases from the original text, have long been a popular choice, but these summaries suffer from being incohesive and disjointed. More recently, abstractive approaches to ATS have gained popularity thanks to advancements in neural text generation. Yet, much of the research
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Kew, T., Kostrzewa, M., & Ebling, S. (2023). 20 Minuten: A Multi-task News Summarisation Dataset for German. Proceedings of the Swiss Text Analytics Conference, 1–13. https://aclanthology.org/2023.swisstext-1.1
