Prompting
Prompting is a methodological technique in natural language processing whereby a model's behavior is guided through the strategic formulation of input texts to elicit desired responses, distinguished from other control mechanisms by its reliance on implicit structural cues rather than explicit programming or architectural modification.
782
Publications
61.7K
Citations
2.7K
Authors
756
Institutions
Publications per year
2017–2026
413
Parents
782
A relational model of data for large shared data banks
E. F. Codd · Communications of the ACM · 1970 · 5.2K citations · Full text
A relational model of data for large shared data banks
E. F. Codd · Communications of the ACM · 1983 · 4.8K citations
Large Language Models are Zero-Shot Reasoners
Takeshi Kojima, Shixiang Gu, Machel Reid et al. · arXiv (Cornell University) · 2022 · 1.1K citations · Full text
Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Prompts
J.D. Zamfirescu-Pereira, Richmond Y. Wong, Bjoern Hartmann et al. · 2023 · 799 citations · Full text
Computing, Computer Science, Design +17
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University of Kentucky
Lexington, United States
19 h-index
48 publications
2K citations
University of Washington
Seattle, United States
16 h-index
52 publications
3.9K citations

University of North Carolina at Charlotte
Charlotte, United States
16 h-index
45 publications
4.6K citations

Anadolu University
Eskişehir, Türkiye
14 h-index
26 publications
896 citations

Vanderbilt University
Nashville, United States
14 h-index
43 publications
2.1K citations

University of Toronto
Toronto, Canada
11 h-index
49 publications
3.3K citations
University of Pittsburgh
Pittsburgh, United States
9 h-index
19 publications
1.2K citations
Harvard University
Cambridge, United States
9 h-index
30 publications
5.4K citations
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Repository · 118 publications · 13K citations
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JABA · 44 publications · 2.8K citations
34
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12 publications · 396 citations
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JSET · 9 publications · 306 citations
9
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EC · 9 publications · 948 citations
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