Jan. 16, 2022, 12:13 p.m. | /u/Tarang_Soni

Natural Language Processing www.reddit.com

Recently, I was reading some literature about text summarization and came across its evaluation metric, the "ROUGE" score. From what I understood from preliminary reading, the ROUGE score only measures n-gram overlap between candidate summary and reference summary which wrongly penalizes abstractive summaries containing different n-grams but conveying the same meaning. There's also a BERTScore metric (arXiv'19, ICLR'20) that does not suffer from these issues of ROUGE and computes contextual similarity rather than just n-gram overlap. How can I assess …

languagetechnology text text summarization

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