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Most visual computation in VLMs is redundant, allowing for a 55% FLOP reduction with minimal accuracy loss by simply bypassing token-specific projections in early and late layers.
Moxin 7B and its variants (VLM, VLA, Chinese) offer a new suite of fully transparent, open-source multimodal models, pushing beyond simple weight sharing to enable deeper customization and collaborative research.