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VibeVideoBench:Evaluating Multimodal Agents on Code-Driven Video Generation

Paper recorded by Signals 4 on 2026-10-26 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-26 on arXiv · recorded by Signals 4 on 2026-10-27

Category: cs.CV · 计算机视觉 · first seen 2026-10-27

Abstract

Diffusion video models produce striking clips, but they cannot reliably render an exact formula, a correct chart, a ruleconsistent game or narration synchronized to on-screen events. A different route is emerging: multimodal agents that write code to render every frame and synthesize every sound. We introduce VibeVideoBench, a benchmark for evaluating agents on code-driven video generation. Its 23

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#124 most recent of 739 cs.CV papers we have recorded · ↑ newer: When Visual Evidence Is Insufficient: How Instructions, Post-Training, · ↓ older: Do vision models know that three is three?
Cite this page: VibeVideoBench:Evaluating Multimodal Agents on Code-Driven Video Generation: the #124 most recent of 739 cs.CV papers we have recorded (as of 2026-10-26). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/vibevideobench-evaluating-multimodal-agents-on-code-driven-video-generation.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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