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  1. Are machines radically contextualist?Ryan M. Nefdt - 2023 - Mind and Language 38 (3):750-771.
    In this article, I describe a novel position on the semantics of artificial intelligence. I present a problem for the current artificial neural networks used in machine learning, specifically with relation to natural language tasks. I then propose that from a metasemantic level, meaning in machines can best be interpreted as radically contextualist. Finally, I consider what this might mean for human‐level semantic competence from a comparative perspective.
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  • Taking truth seriously: the case of generics.Martin Gustafsson - 2023 - Synthese 202 (1):1-28.
    By discussing a large number of different examples, this paper argues that the class of so-called generic statements is much more heterogeneous that is usually recognized in the contemporary debate. It is claimed that the theoretical tendency towards overgeneralization or homogenization makes it impossible to adequately understand how generic statements function in language and to handle the dangers involved in generics that express and promote social stereotypes and prejudices. It is also argued that such overgeneralization involves what J. L. Austin (...)
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