ProRefine: Inference-Time Prompt Refinement with Textual Feedback
Published 6 Nov 2025 · arXiv · Deepak Pandita
Overview
ProRefine is an innovative method for optimizing AI prompts at inference-time using textual feedback. It significantly improves the accuracy of AI models in multi-step reasoning tasks without additional training.
Key Insights
- Improvement in Accuracy: ProRefine enhances model accuracy by 3 to 37 percentage points over zero-shot Chain-of-Thought baselines. This is based on evaluations using five benchmark mathematical reasoning datasets.
- Cost-Effectiveness: Smaller AI models can achieve performance levels similar to larger models, reducing costs and democratizing access to high-performing AI systems.
- No Additional Training Required: The method does not require extra training or ground truth labels, making it efficient and scalable.
BFSI Relevance
- Why Relevant: The ability to improve AI model accuracy and efficiency is crucial for financial services that rely on complex reasoning, such as fraud detection and risk assessment.
- Primary Sector: Financial Services
- Subsectors: Asset Management, Risk Management
- Actionable Implications: BFSI professionals should consider integrating ProRefine to enhance AI-driven decision-making processes, potentially reducing costs and improving service delivery.
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