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CLIP models, despite their prowess, stumble when understanding 360掳 images, failing to maintain semantic alignment under horizontal circular shifts.
Subtracting the mean from activations unlocks stable FP4 training for LLMs, closing the performance gap with BF16 without complex spectral methods.
