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A Unified Account of Concepts and Chunks

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Computer Science > Computation and Language

arXiv:2609.30414 (cs)
[Submitted on 24 Sep 2026]

Title:A Unified Account of Concepts and Chunks

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Abstract:Cognitive psychology has studied how people encode, use, and learn concepts that describe categories, and how they represent, recognize, and acquire chunks for familiar patterns of elements. The literatures on these two topics are nearly disjoint, which poses a challenge for unified theories of cognition. In this paper, we review Cobweb, a computational account of categorization and concept formation, and propose an extended theory that incorporates chunks and their acquisition. The theory makes no commitments about modality, applying to any experience that decomposes into elements and relations among them. We also present \trellis/, an implementation of this theory, and illustrate its application to learning context-free grammars, which we adopt as a testbed because they involve both concept-like and chunk-like elements. In addition, we report experimental results on three synthetic grammars that demonstrate the system's ability to represent syntactic knowledge, use it to parse and generate sentences, and learn compositional structures from sample parses. We conclude by discussing related work on concepts and chunks, along with directions for future research in the area.
Comments: Accepted to ACS-26 (oral presentation)
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2609.30414 [cs.CL]
  (or arXiv:2609.30414v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2609.30414
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Karthik Singaravadivelan [view email]
[v1] Thu, 24 Sep 2026 18:10:43 UTC (190 KB)
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