Unmasking VLM Vulnerabilities: A Blueprint for Interpretable Failure Analysis

This blueprint outlines a research agenda focused on systematically identifying and explaining the failure modes of Vision-Language Models (VLMs). We propose a structured approach to categorize errors, link them to specific model components, and develop interpretable explanations for why these failures occur, moving beyond superficial accuracy metrics.