Back to search

Article

PRIME: Prompt Refinement via Information-driven Methods and Expansion, A Modular Framework for Context-Aware Prompt Amplification

2026-01-27

Abstract excerpt

<title>Abstract</title> <p>While Large Language Models (LLMs) have transformed natural language processing, their effectiveness depends critically on prompt quality. Current Retrieval-Augmented Generation (RAG) systems retrieve documents to generate answers; we propose a fundamentally different approach: using retrieval to construct better questions. This paper introduces PRIME (Prompt Refinement via Information-...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
7fb8b05b-702a-5bd1-bf6d-7044c62347e1
DOI
10.21203/rs.3.rs-8655520/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
PRIME: Prompt Refinement via Information-driven Methods and Expansion, A Modular Framework for Context-Aware Prompt AmplificationDOI 10.21203/rs.3.rs-8655520/v1
Select a neighboring publication to make it the new centre.