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FilmBench reveals that leading video generation models fall short of cinematic standards, scoring significantly lower than on traditional benchmarks, which could redefine how we evaluate AI-generated video quality.
Seedance 2.0 leapfrogs existing models by unifying multi-modal inputs (text, image, audio, video) into a single architecture for generating high-quality, longer-duration audio-video content.
Image generation models exhibit a surprising "Order-to-Space Bias," meaning the order you mention objects in a prompt can drastically alter their placement in the generated image, even overriding other visual cues.
