MLLMs for Video Content Analysis
Evaluating AI's Understanding of Abstract Concepts in Mental Health Videos
This study explores how Multimodal Large Language Models (MLLMs) can interpret abstract concepts in YouTube Shorts about depression, comparing AI analysis to human understanding.
- First investigates MLLM capabilities for analyzing visual content beyond literal description
- Tests LLaVA-1.6 Mistral 7B's ability to interpret four abstract concepts in depression-related videos
- Reveals both strengths and limitations of current MLLMs in understanding nuanced concepts
- Provides a methodological framework for future MLLM-based video analysis
For healthcare professionals, this research demonstrates the potential and limitations of using AI to analyze mental health-related social media content at scale, which could support early intervention and public health monitoring.