Text Generation
Text Generation is the computational process within Natural Language Processing whereby a system produces coherent and contextually appropriate natural language text from structured or unstructured input, distinguished from related linguistic modeling tasks by its primary focus on the automated creation of human-readable textual output.
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2017–2026
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7.1K
ROUGE: A Package for Automatic Evaluation of Summaries
Chin-Yew Lin · 2004 · 8.3K citations
Show and tell: A neural image caption generator
Oriol Vinyals, Alexander Toshev, Samy Bengio et al. · 2015 · 6.4K citations
Toward a model of text comprehension and production.
Walter Kintsch, Teun A. van Dijk · Psychological Review · 1978 · 5K citations
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang et al. · arXiv (Cornell University) · 2022 · 4.3K citations · Full text
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2.3K
Google (United States)
Mountain View, United States
56 h-index
583 publications
127.9K citations
Carnegie Mellon University
Pittsburgh, United States
56 h-index
419 publications
29.7K citations
Microsoft (United States)
Redmond, United States
55 h-index
360 publications
50.6K citations

Peking University
Beijing, China
54 h-index
519 publications
31.4K citations
Stanford University
Stanford, United States
52 h-index
241 publications
50.1K citations

University of Edinburgh
Edinburgh, United Kingdom
51 h-index
240 publications
19.8K citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
48 h-index
294 publications
23.6K citations
Tsinghua University
Beijing, China
46 h-index
338 publications
31K citations
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Repository · 1.1K publications · 78.8K citations
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Conference · 190 publications · 12.3K citations
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40 publications · 5K citations
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TACL · 36 publications · 3.3K citations
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Conference · 49 publications · 3.6K citations
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