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Extending Multi-Document Summarization Evaluation to the Interactive Setting
2021
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
unpublished
Allowing users to interact with multidocument summarizers is a promising direction towards improving and customizing summary results. Different ideas for interactive summarization have been proposed in previous work but these solutions are highly divergent and incomparable. In this paper, we develop an end-to-end evaluation framework for interactive summarization, focusing on expansion-based interaction, which considers the accumulating information along a user session. Our framework includes a
doi:10.18653/v1/2021.naacl-main.54
fatcat:yiiwmt2ndfdq3kstob4i4nlo5e