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Neural Text Summarization: A Critical Evaluation
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Text summarization aims at compressing long documents into a shorter form that conveys the most important parts of the original document. Despite increased interest in the community and notable research effort, progress on benchmark datasets has stagnated. We critically evaluate key ingredients of the current research setup: datasets, evaluation metrics, and models, and highlight three primary shortcomings: 1) automatically collected datasets leave the task underconstrained and may contain
doi:10.18653/v1/d19-1051
dblp:conf/emnlp/KryscinskiKMXS19
fatcat:oex3xjc3frh5xcxz7qonuvi2gq