MAVEN A Multi-Agent Framework for Multicultural Text-to-Video Generation

• URL: http://arxiv.org/abs/2605.16716v1
• Date: Sat, 16 May 2026 00:01:18 GMT
• Title: MAVEN A Multi-Agent Framework for Multicultural Text-to-Video Generation
• Abstract summary: MAVEN is a multi-agent prompt refinement framework.<n>It decomposes prompts into person, action, and location dimensions.<n>It improves cultural fidelity in both mono-cultural and cross-cultural T2V generation.
• Score: 7.901765633133679
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Text-to-video (T2V) generation has rapidly progressed in visual fidelity, yet its ability to faithfully represent multiple cultures within a single prompt remains underexplored. We introduce MAVEN, a multi-agent prompt refinement framework designed to improve cultural fidelity in both mono-cultural and cross-cultural T2V generation. MAVEN decomposes prompts into person, action, and location dimensions, handled by specialized agents operating in parallel or sequentially. To support systematic evaluation, we contribute a new benchmark of 243 culturally grounded prompts and 972 corresponding videos, spanning three cultures (Chinese, American, Romanian), three action categories, and both mono-cultural and cross-cultural scenarios. Evaluations combining CLIP-based metrics, VLM-as-judge assessments, and videoquality measures show that multi-agent refinement, particularly parallel specialization, significantly improves cultural relevance while preserving visual quality and temporal consistency. The dataset and code are available athttps://github.com/AIM-SCU/CRAFT

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