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ACL Findings2021

Is Human Scoring the Best Criteria for Summary Evaluation?

Oleg V. Vasilyev, John Bohannon

摘要

A summary quality measure is judged by how well it correlates with quality scores produced by human annotators. A higher correlation with human scores is considered to be a decisive indicator of a better measure. In this work we present observations that cast doubt on this view. We also show a possibility of an alternative indicator for selecting the best measure from a family of measures, a criterion that does not rely on human scores.

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它引用的 Paper6

  1. BERTScore: Evaluating Text Generation with BERTTianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger 等ICLR 2020 · 8,443 次引用
  2. FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive SummarizationEsin Durmus, He He, Mona T. DiabACL 2020 · 90 次引用
  3. GO FIGURE: A Meta Evaluation of Factuality in SummarizationSaadia Gabriel, Asli Celikyilmaz, Rahul Jha, Yejin Choi 等ACL Findings 2021 · 75 次引用
  4. What Have We Achieved on Text Summarization?Dandan Huang, Leyang Cui, Sen Yang, Guangsheng Bao 等EMNLP 2020 · 72 次引用
  5. Evaluating the Factual Consistency of Abstractive Text SummarizationWojciech Kryscinski, Bryan McCann, Caiming Xiong, Richard SocherEMNLP 2020 · 67 次引用

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