Exemplar-based learning requires: (1) a segmentation procedure for identifying the units of past experiences that a present experience can be compared to, and (2) a similarity function for comparing these past experiences to the present experience. This article argues that for a learner to learn a language these two mechanisms will require abstractions such as linguistic features. Moreover, because the segmentation procedure will vary depending on the language, a radical exemplar theory is likely to require linguistic abstractions for learning. [For Ben Ambridge's "Against Stored Abstractions: A Radical Exemplar Model of Language Acquisition," see EJ1269951.]