ConfLVLM introduces a groundbreaking approach to guarantee factual accuracy when AI models interpret images and generate text.

• Creates statistical confidence scores to identify potential hallucinations
• Provides verifiable accuracy guarantees for generated content
• Demonstrates effectiveness across multiple domains including medical radiology reports
• Addresses a critical barrier to reliable AI deployment in high-stakes environments

For healthcare applications, this research represents a significant advancement toward trustworthy AI for medical imaging interpretation, potentially reducing diagnostic errors and improving patient safety.

Towards Statistical Factuality Guarantee for Large Vision-Language Models