SNNLP: Energy-Efficient Natural Language Processing Using Spiking Neural Networks

As spiking neural networks receive more attention, we look toward applications of this computing paradigm in fields other than computer vision and signal processing. One major field, underexplored in the neuromorphic setting, is Natural Language Processing (NLP), where most state-of-the-art solutions still heavily rely on resource-consuming and power-hungry traditional deep learning architectures. Therefore, it is compelling to design NLP models for neuromorphic architectures due to their low energy requirements, with the additional benefit of a more human-brain-like operating model for …

applications art attention computer computer vision computing cs.cl deep learning energy fields language language processing look major natural natural language natural language processing networks neural networks neuromorphic nlp paradigm power processing signal solutions spiking neural networks state vision