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Reasoning with Language Model Prompting: A Survey

Authors :
Qiao, Shuofei
Ou, Yixin
Zhang, Ningyu
Chen, Xiang
Yao, Yunzhi
Deng, Shumin
Tan, Chuanqi
Huang, Fei
Chen, Huajun
Publication Year :
2022

Abstract

Reasoning, as an essential ability for complex problem-solving, can provide back-end support for various real-world applications, such as medical diagnosis, negotiation, etc. This paper provides a comprehensive survey of cutting-edge research on reasoning with language model prompting. We introduce research works with comparisons and summaries and provide systematic resources to help beginners. We also discuss the potential reasons for emerging such reasoning abilities and highlight future research directions. Resources are available at https://github.com/zjunlp/Prompt4ReasoningPapers (updated periodically).<br />Comment: ACL 2023, 24 pages, add references of theoretical analysis

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2212.09597
Document Type :
Working Paper