Language-Guided Graph Representation Learning for Video Summarization

A recent study examined the preferences of large language models (LLMs) in resolving knowledge conflicts, revealing a tendency to favor information from credible sources like government and newspaper outlets over social media. This research utilized a novel framework to analyze how these source preferences influence LLM outputs.

The MLLM-VADStory framework has been introduced to enhance the understanding of video ad storylines by systematically quantifying and generating insights based on domain knowledge. This innovative approach segments ads into functional units and classifies their roles, ultimately improving video retention through story-based creatives.