Mitigating the Impact of Reference Quality on Evaluation of Summarization Systems with Reference-Free Metrics

• URL: http://arxiv.org/abs/2410.10867v1
• Date: Tue, 08 Oct 2024 11:09:25 GMT
• Title: Mitigating the Impact of Reference Quality on Evaluation of Summarization Systems with Reference-Free Metrics
• Authors: Théo Gigant, Camille Guinaudeau, Marc Decombas, Frédéric Dufaux,
• Abstract summary: We introduce a reference-free metric that correlates well with human evaluated relevance, while being very cheap to compute. We show that this metric can also be used alongside reference-based metrics to improve their robustness in low quality reference settings.
• Score: 4.881135687863645
• License:
• Abstract: Automatic metrics are used as proxies to evaluate abstractive summarization systems when human annotations are too expensive. To be useful, these metrics should be fine-grained, show a high correlation with human annotations, and ideally be independent of reference quality; however, most standard evaluation metrics for summarization are reference-based, and existing reference-free metrics correlate poorly with relevance, especially on summaries of longer documents. In this paper, we introduce a reference-free metric that correlates well with human evaluated relevance, while being very cheap to compute. We show that this metric can also be used alongside reference-based metrics to improve their robustness in low quality reference settings.

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