Titlebook: Cognitive Plausibility in Natural Language Processing; Lisa Beinborn,Nora Hollenstein Book 2024 The Editor(s) (if applicable) and The Auth

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Remarks Honoring Dr. Edward E. Jones,ion signals. In the second part, we introduce methods to link these interpretability metrics to phenomena that we observe in cognitive signals. We then discuss how we can adjust the target objective and the inductive bias of the model towards cognitively more plausible procedural patterns.

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978-3-031-43262-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Introduction: Self-Action Models, collect differ with respect to temporal accuracy, the degree of consciousness involved, and the levels of linguistic processing they reflect. We showcase how the research question affects the choice of the most suitable cognitive signal type.

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Book 2024he authors present the idea that more can be learned about cognitive plausibility of computational language models by linking signals of cognitive processing load in humans to interpretability methods that allow for exploration of the hidden mechanisms of neural models. The book identifies limitatio