PRISM: Prompt-Refined In-Context System Modelling for Financial Retrieval

📰 ArXiv cs.AI

PRISM is a training-free framework for financial information retrieval using prompt-refined in-context system modeling

advanced Published 7 Apr 2026
Action Steps
  1. Utilize large language models (LLMs) as a foundation for financial information retrieval
  2. Implement refined system prompting to improve the accuracy of extracted information
  3. Apply in-context learning (ICL) to adapt to specific financial retrieval tasks
  4. Integrate lightweight multi-agent coordination for efficient document and chunk ranking
Who Needs to Know This

Data scientists and AI engineers on a team can benefit from PRISM as it enables efficient extraction of task-relevant information from financial filings, while product managers can leverage it for informed decision-making

Key Insight

💡 PRISM enables efficient extraction of task-relevant information from financial filings without requiring training data

Share This
📊 PRISM: a training-free framework for financial info retrieval using prompt-refined in-context system modeling
Read full paper → ← Back to Reads