Search-Based Generation Techniques for Improving LLM Responses: A Comparative Study of Zero-shot and RAG on GPT-3.5 and GPT-4
Domestic Conferences & Theses
Authors
Joongmin Shin*, Jungun Lee
Abstract
A comparative study on zero-shot versus retrieval-augmented generation setups for GPT-3.5 and GPT-4. The analysis outlines reliability and practical implementation benefits of evidence-grounded generation.
Key Contribution
Comparative analysis of zero-shot vs. RAG for GPT models, demonstrating benefits of evidence-grounded generation.