The authors argue that Ambridge's radical exemplar account of language cannot clearly explain all syntactic priming evidence, such as inverse preference effects ("greater" priming for less frequent structures), and the contrast between short-lived lexical boost and long-lived abstract priming. Moreover, without recourse to a level of…

Short term memory (STM) and working memory (WM) performance consistently predict language abilities in children with developmental language disorders. However, causality is not fully established. Moreover, evidence from the fine-grained analysis of STM/WM tasks and comprehension of complex sentences, suggests that long term memory (LTM)…

In this commentary on the Special Issue, I will address the question of what memory spans measure concerning language, as language has, at least, a linear and a hierarchical dimension. I suggest that if anything what is measured has to do with the linear dimension. Then, I will discuss the welcome results on bilingual children with language…

The research studies presented in this special issue rest on two assumptions: firstly, that limitations in verbal short-term memory and verbal working memory (vSTM/WM) capacity are likely to be related to impairments in syntax, and secondly that this relationship is likely to be causal, with impairments in vSTM/WM causing impairments in syntax. In…

The radical exemplar model resonates with work on perceptual classification and categorization highlighting the role of exemplars in memory representations. Further development of the model requires acknowledgment of both the fleeting and fragile nature of perceptual representations and the gist-based, good-enough quality of long-term memory…

Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…

In 'Against Stored Abstractions,' Ambridge uses neural and computational evidence to make his case against abstract representations. He argues that storing only exemplars is more parsimonious -- why bother with abstraction when exemplar models with on-the-fly calculation can do everything abstracting models can and more -- and implies that his…

Ambridge argues that there is widespread agreement among child language researchers that learners store linguistic abstractions. In this commentary the authors first argue that this assumption is incorrect; anti-representationalist/exemplar views are pervasive in theories of child language. Next, the authors outline what has been learned from this…