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Operationalising Representation in Natural Language Processing
Despite its centrality in the philosophy of cognitive science, there has been little prior philosophical work engaging with the notion of representation in contemporary NLP practice.
Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information
We show that `diagnostic classifiers', trained to predict number from the internal states of a language model, provide a detailed understanding of how, when, and where this information is represented.
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