Evaluation Of Text Generation
Evaluation of Text Generation is a scholarly methodological framework that systematizes the assessment of generated textual outputs by establishing criteria, metrics, and benchmarks to determine fidelity, coherence, relevance, and quality relative to human language expectations.
551
Publications
37.6K
Citations
1.8K
Authors
517
Institutions
Publications per year
2017–2026
395
Parents
551
BERTScore: Evaluating Text Generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu et al. · arXiv (Cornell University) · 2019 · 2K citations · Full text
The Curious Case of Neural Text Degeneration
Ari Holtzman, Jan Buys, Li Du et al. · arXiv (Cornell University) · 2019 · 1.1K citations · Full text
Ismail Dergaa, Karim Chamari, Piotr Żmijewski et al. · Biology of Sport · 2023 · 741 citations · Full text
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University of Edinburgh
Edinburgh, United Kingdom
21 h-index
59 publications
4.2K citations
Carnegie Mellon University
Pittsburgh, United States
18 h-index
84 publications
3.3K citations

University of Aberdeen
Aberdeen, United Kingdom
17 h-index
39 publications
2.3K citations
University of Washington
Seattle, United States
17 h-index
46 publications
8.8K citations
Google (United States)
Mountain View, United States
17 h-index
101 publications
5.1K citations
University of Brighton
Brighton, United Kingdom
15 h-index
23 publications
1.4K citations
Microsoft (United States)
Redmond, United States
15 h-index
50 publications
6.3K citations
Stanford University
Stanford, United States
15 h-index
50 publications
6K citations
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Repository · 97 publications · 8.1K citations
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Conference · 9 publications · 449 citations
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9 publications · 856 citations
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Conference · 9 publications · 251 citations
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6 publications · 724 citations
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