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DiVid: Diagnosing Dimension-Specific Diversity Collapse in Video Generation Models
Despite remarkable progress, video generation models often produce highly similar outputs when repeatedly sampled from the same prompt, limiting their usefulness for creative exploration. Existing diversity evaluations primarily rely on global scalar metrics, which obscure where diversity collapses
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