multibind-attribute-misbinding-benchmark

【效率与协作】Evaluate multi-reference image generation fidelity using MultiBind's dimension-wise confusion framework. Detects cross-subject attribute errors that holistic metrics (FID, CLIP) miss, including drift (degradation), swap (permutation), dominance (interference), and blending (averaging). Protocol uses specialist models for face identity, appearance, po…

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