基本信息
- 来源: arxiv
- 原始来源: https://arxiv.org/abs/2603.11048v1
- 作者: Susung Hong, Brian Curless, Ira Kemelmacher-Shlizerman, Steve Seitz
- 分类: cs.CV
- 论文时间: 2026-03-11T17:59:59Z
- 论文 PDF: https://arxiv.org/pdf/2603.11048v1.pdf
来源摘要/节选
We propose a fully automated AI system that produces short comedic videos similar to sketch shows such as Saturday Night Live. Starting with character references, the system employs a population of agents loosely based on real production studio roles, structured to optimize the quality and diversity of ideas and outputs through iterative competition, evaluation, and improvement. A key contribution is the introduction of LLM critics aligned with real viewer preferences through the analysis of a corpus of comedy videos on YouTube to automatically evaluate humor. Our experiments show that our framework produces results approaching the quality of professionally produced sketches while demonstrating state-of-the-art performance in video generation.
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