Sentence Mover’s Similarity: Automatic Evaluation for Multi-Sentence Texts
Article Status
Published
Authors/contributors
- Clark, Elizabeth (Author)
- Celikyilmaz, Asli (Author)
- Smith, Noah A. (Author)
Title
Sentence Mover’s Similarity: Automatic Evaluation for Multi-Sentence Texts
Date
2019
Proceedings Title
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Conference Name
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Place
Florence, Italy
Publisher
Association for Computational Linguistics
Pages
2748-2760
Language
en
Short Title
Sentence Mover’s Similarity
Accessed
27/10/2023, 17:09
Library Catalogue
DOI.org (Crossref)
Extra
<AI Smry>: This work introduces methods based on sentence mover’s similarity, and finds that sentence-based metrics correlate with human judgments significantly better than ROUGE, both on machine-generated summaries and human-authored essays.
Citation
Clark, E., Celikyilmaz, A., & Smith, N. A. (2019). Sentence Mover’s Similarity: Automatic Evaluation for Multi-Sentence Texts. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2748–2760. https://doi.org/10.18653/v1/P19-1264
Technical methods
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