Strong systematicity in sentence processing by simple recurrent networks


Providing explanations of language comprehension requires models that describe language processing and display strong systematicity. Although various extensions of connectionist models have been suggested in order to account for this phenomenon, we found that even a simple recurrent network that had been trained in a way that can be considered `standard', could display strong systematicity. This ability was found to result from informative word representations that developed in the network.

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