Vector Symbolic Architectures for Context-Free Grammars

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Abstract

Vector symbolic architectures (VSA) are a viable approach for the hyperdimensional representation of symbolic data, such as documents, syntactic structures, or semantic frames. We present a rigorous mathematical framework for the representation of phrase structure trees and parse trees of context-free grammars (CFG) in Fock space, i.e. infinite-dimensional Hilbert space as being used in quantum field theory. We define a novel normal form for CFG by means of term algebras. Using a recently developed software toolbox, called FockBox, we construct Fock space representations for the trees built up by a CFG left-corner (LC) parser. We prove a universal representation theorem for CFG term algebras in Fock space and illustrate our findings through a low-dimensional principal component projection of the LC parser state. Our approach could leverage the development of VSA for explainable artificial intelligence (XAI) by means of hyperdimensional deep neural computation.

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Graben, P. beim, Huber, M., Meyer, W., Römer, R., & Wolff, M. (2022). Vector Symbolic Architectures for Context-Free Grammars. Cognitive Computation, 14(2), 733–748. https://doi.org/10.1007/s12559-021-09974-y

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