Scribby: A Multi-Level LLM Framework for Semantic Video Analysis
As video content continues to expand across educational platforms, recorded lectures, and live-streamed entertainment, the need for efficient and structured analysis of long-form footage has increased \cite{1}. Although many existing AI programs provide high-level video summaries based on AI-generated transcripts \cite{2,3,4,5}, these approaches are often limited to coarse overviews and lack detailed analysis of a video's structure, thematic progression, and semantic relationships, all of which are required for comprehensive video analysis. This paper proposes an LLM-based video summarization framework that balances macro-level comprehension with micro-level semantic analysis \cite{6,12,1...
| Authors | Julian Abelarde, Hugo Garrido-Lestache Belinchon |
|---|---|
| Primary category | cs.CV |
| Published | 8 June 2026 |
| Last updated at source | 8 June 2026 |
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