Query Expansion by Prompting Large Language Models

Understand

Query expansion is a widely used technique to improve the recall of search systems.

• In this paper, we propose an approach to query expansion that leverages the generative abilities of Large Language Models (LLMs).
• Unlike traditional query expansion approaches such as Pseudo-Relevance Feedback (PRF) that relies on retrieving a good set of pseudo-relevant documents to expand queries, we rely on the generative and creative abilities of an LLM and leverage the knowledge inherent in the model.
• We study a variety of different prompts, including zero-shot, few-shot and Chain-of-Thought (CoT).