This research introduces a novel approach to help AI systems better interpret human emotions, intentions, and behaviors in video content.

• Leverages iterative loop structures with large language models to enhance video question answering
• Creates AI systems that can more naturally integrate visual and verbal information
• Addresses key challenges in developing socially intelligent AI for human interaction
• Particularly valuable for applications requiring nuanced understanding of human behavior

Medical Impact: This advancement could transform healthcare settings by enabling AI systems to better interpret patient emotions and non-verbal cues, potentially improving diagnostic processes and patient-provider interactions in caregiving environments.

Leveraging LLMs with Iterative Loop Structure for Enhanced Social Intelligence in Video Question Answering