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May 6, 2023 · Tianqiang Yan, Tiansheng Xu. In this paper, we propose a simple yet efficient approach based on prompt engineering that leverages the large language model itself to optimize its answers without relying on auxiliary models.
- arXiv:2305.04039 [cs.CL]
Articles 1–20. Shanghai Advanced Research Institute, Chinese Academy of Sciences - Cited by 600 - Mobile Communications - Cognitive Radio Networks - Spectrum Sensing.
Affiliations: [Faculty of Natural Sciences, Imperial College London].
Tiansheng Xu. Affiliation. School of Management and Engineering, Capital University of Economics and Business, Beijing. Publication Topics share prices,stock markets ...
Read Tiansheng Xu's latest research, browse their coauthor's research, and play around with their algorithms
Tianheng Xu (Member, IEEE) received the Ph.D. degree from the Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China, in 2016. He is currently an Associate Professor with the Shanghai Advanced Research Institute, Chinese Academy of Sciences.
1 code implementation • 6 May 2023 • Tianqiang Yan, Tiansheng Xu In this paper, we propose a simple yet efficient approach based on prompt engineering that leverages the large language model itself to optimize its answers without relying on auxiliary models.
