Publication: German Also Hallucinates! Inconsistency Detection in News Summaries with the Absinth Dataset
German Also Hallucinates! Inconsistency Detection in News Summaries with the Absinth Dataset
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Mascarell, L., Chalumattu, R., & Rios, A. (2024). German Also Hallucinates! Inconsistency Detection in News Summaries with the Absinth Dataset. 7696–7706. https://aclanthology.org/2024.lrec-main.680/
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The advent of Large Language Models (LLMs) has led to remarkable progress on a wide range of natural language processing tasks. Despite the advances, these large-sized models still suffer from hallucinating information in their output, which poses a major issue in automatic text summarization, as we must guarantee that the generated summary is consistent with the content of the source document. Previous research addresses the challenging task of detecting hallucinations in the output (i.e. inconsistency detection) in order to evaluate
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Mascarell, L., Chalumattu, R., & Rios, A. (2024). German Also Hallucinates! Inconsistency Detection in News Summaries with the Absinth Dataset. 7696–7706. https://aclanthology.org/2024.lrec-main.680/
