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OmniDelta achieves a 1.64x speedup in inference while reducing GPU memory usage by 22% at just 25% token retention, redefining efficiency in OmniLLMs.
Co-training item embeddings in recommendation systems can boost prediction accuracy and engagement while slashing computational costs by 30%.
