@inproceedings{larsson-etal-2025-finding,
    title = "Finding Answers to Questions: Bridging between Type-based and Computational Neuroscience Approaches",
    author = {Larsson, Staffan  and
      Ginzburg, Jonathan  and
      Cooper, Robin  and
      L{\"u}cking, Andy},
    editor = "Evang, Kilian  and
      Kallmeyer, Laura  and
      Pogodalla, Sylvain",
    booktitle = "Proceedings of the 16th International Conference on Computational Semantics",
    month = sep,
    year = "2025",
    address = {D{\"u}sseldorf, Germany},
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/2025.iwcs-1.12/",
    pages = "128--136",
    ISBN = "979-8-89176-316-6",
    abstract = "The paper outlines an account of how the brain might process questions and answers in linguistic interaction, focusing on accessing answers in memory and combining questions and answers into propositions. To enable this, we provide an approximation of the lambda calculus implemented in the Semantic Pointer Architecture (SPA), a neural implementation of a Vector Symbolic Architecture. The account builds a bridge between the type-based accounts of propositions in memory (as in the treatments of belief by Ranta (1994) and Cooper (2023) and the suggestion for question answering made by Eliasmith (2013) question answering is described in terms of transformations of structured representations in memory providing an answer. We will take such representations to correspond to beliefs of the agent. On Cooper{'}s analysis, beliefs are considered to be types which have a record structure closely related to the structure which Eliasmith codes in vector representations (Larsson et al, 2023). Thus the act of answering a question can be seen to have a neural base in a vector transformation translatable in Eliasmith{'}s system to activity of spiking neurons and to correspond to using an item in memory (abelief) to provide an answer to the question."
}