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CoRA achieves effective task-conditioned retrieval on-device without the need for retriever fine-tuning or backpropagation, revolutionizing how we approach in-context learning.
Achieving 97.2% accuracy on N-MNIST while consuming only 0.8 pJ/SOP could redefine energy-efficient neuromorphic computing.
By intelligently suppressing boundary outliers before quantization, BS-KMQ slashes quantization error by 3x and boosts energy efficiency by 24x in in-memory computing.
