Generalising to German Plural Noun Classes, from the Perspective of a Recurrent Neural Network
Abstract Inflectional morphology has since long been a useful testing ground for broader questions about generalization in language and the viability of neural network models as cognitive models of language. Here, in line with that tradition, we explore how recurrent neural networks acquire the complex German plural system and reflect upon how their strategy compares to human generalization and rule-based models of this system. We perform analyses including behavior experiments, diagnostic classification, representation analysis and causal interventions, suggesting that the […]
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