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Found 4 papers, 0 papers with code
Attention-Driven Training-Free Efficiency Enhancement of Diffusion Models
Specifically, for single-denoising-step pruning, we develop a novel ranking algorithm, Generalized Weighted Page Rank (G-WPR), to identify redundant tokens, and a similarity-based recovery method to restore tokens for the convolution operation.
Zero-TPrune: Zero-Shot Token Pruning through Leveraging of the Attention Graph in Pre-Trained Transformers
Deployment of Transformer models on edge devices is becoming increasingly challenging due to the exponentially growing inference cost that scales quadratically with the number of tokens in the input sequence.
Electromagnetic Sensor and Actuator Attacks on Power Converters for Electric Vehicles
voltage and current sensor outputs and gate control signals.
Cryptography and Security
A New MRAM-based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision
The excellent performance of modern deep neural networks (DNNs) comes at an often prohibitive training cost, limiting the rapid development of DNN innovations and raising various environmental concerns.
