COMIC: Agentic Sketch Comedy Generation
Susung Hong, Brian Curless, Ira Kemelmacher-Shlizerman, Steve Seitz

TL;DR
COMIC is an automated AI system that generates short comedic videos by simulating production roles, using large language model critics aligned with viewer preferences, achieving high-quality results comparable to professional sketches.
Contribution
The paper introduces a novel AI framework for comedy video creation that combines agent-based role simulation with LLM critics trained on viewer preferences.
Findings
Produces comedy videos approaching professional quality
Demonstrates state-of-the-art video generation performance
Aligns humor evaluation with viewer preferences
Abstract
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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Taxonomy
TopicsMultimodal Machine Learning Applications · Humor Studies and Applications · Artificial Intelligence in Games
