The Unstoppable Rise of Computational Linguistics in Deep Learning

In this paper, we trace the history of neural networks applied to natural language understanding tasks, and identify key contributions which the nature of language has made to the development of neural network architectures. We focus on the importance of variable binding and its instantiation in attention-based models, and argue that Transformer is not a sequence model but an induced-structure model... (read more)

Results in Papers With Code
(↓ scroll down to see all results)