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Context-Based Prompt Selection Methodology to Enhance Performance in Prompt-Based Learning

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2024, 29(4), pp.9-21
  • DOI : 10.9708/jksci.2024.29.04.009
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : March 11, 2024
  • Accepted : April 4, 2024
  • Published : April 30, 2024

Lib Kim 1 Namgyu Kim 1

1국민대학교

Accredited

ABSTRACT

Deep learning has been developing rapidly in recent years, with many researchers working to utilize large language models in various domains. However, there are practical difficulties that developing and utilizing language models require massive data and high-performance computing resources. Therefore, in-context learning, which utilizes prompts to learn efficiently, has been introduced, but there needs to be clear criteria for effective prompts for learning. In this study, we propose a methodology for enhancing prompt-based learning performance by improving the PET technique, which is one of the contextual learning methods, to select PVPs that are similar to the context of existing data. To evaluate the performance of the proposed methodology, we conducted experiments with 30,100 restaurant review datasets collected from Yelp, an online business review platform. We found that the proposed methodology outperforms traditional PET in all aspects of accuracy, stability, and learning efficiency.

Citation status

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