Structural Persistence in Language Models: Priming as a Window into Abstract Language Representations
Structural Persistence in Language Models: Priming as a Window into Abstract Language Representations
Abstract We investigate the extent to which modern neural language models are susceptible to structural priming, the phenomenon whereby the structure of a sentence makes the same structure more probable in a follow-up sentence. We explore how priming can be used to study the potential of these models to learn …