PIAST: Rapid Prompting with In-context Augmentation for Scarce Training data
Published:Dec 11, 2025 16:55
•1 min read
•ArXiv
Analysis
The article introduces PIAST, a method for improving performance of LLMs when training data is limited. The core idea is to use in-context augmentation and rapid prompting techniques. This is a common problem in LLM development, and this approach offers a potential solution. The source is ArXiv, indicating a peer-reviewed or pre-print research paper.
Key Takeaways
- •PIAST addresses the challenge of limited training data in LLMs.
- •It utilizes in-context augmentation and rapid prompting.
- •The research is published on ArXiv.
Reference
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