LVLM-Interpret: Explaining Decision-Making Processes in Large Vision-Language Models

Understanding the internal mechanisms of large vision-language models (LVLMs) is a complex task. LVLM-Interpret helps users understand the model’s internal decision-making processes, identifying potential responsible artificial intelligence (AI) issues such as biases or incorrect associations. The tool adapts multiple interpretability methods to LVLMs for interactive analysis, including raw attention, relevancy maps, and causal interpretation.