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CLIP models, despite their prowess, stumble when understanding 360° 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.