LATTE: Low-Precision Approximate Attention with Head-wise Trainable Threshold for Efficient Transformer

Jiing-Ping Wang, Ming-Guang Lin, An-Yeu +1

With the rise of Transformer models in NLP and CV domain, Multi-Head Attention has been proven to be a game-changer. However, its expensive computation poses challenges to the mode…