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Found 4 papers, 4 papers with code
Highly Optimized Kernels and Fine-Grained Codebooks for LLM Inference on Arm CPUs
Large language models (LLMs) have transformed the way we think about language understanding and generation, enthralling both researchers and developers.
Restructurable Activation Networks
To address this question, we propose a new paradigm called Restructurable Activation Networks (RANs) that manipulate the amount of non-linearity in models to improve their hardware-awareness and efficiency.
Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge
Autonomous systems are highly vulnerable to a variety of adversarial attacks on Deep Neural Networks (DNNs).
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