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UniSVQ achieves state-of-the-art performance in 2-bit quantization, outperforming traditional methods while enhancing inference speed.
LC-QAT achieves superior performance in 2-bit quantization with just a fraction of the training data, setting a new standard for data-efficient model optimization.
Unlock the Rosetta Stone for neural networks: UAV lets one model explain the inner workings of *any* other, regardless of architecture or size.
By decoupling patch details from semantics, Cheers achieves state-of-the-art multimodal performance at 20% of the training cost of comparable models.
