Paper

Tensor Product Representations of Regular Transductions

Authors
  • Zhouyi Sun (Massachusetts Institute of Technology)
  • Jonathan Rawski (Massachusetts Institute of Technology; San Jose State University)

Abstract

This paper provides a vector space characterization of regular transductions. We use finite model theory to characterize objects like strings and trees as relational structures and origin graphs to characterize input-output relations generated by transducer. We show detailed processes of using multilinear maps as function application for evaluation to compile regular transductions characterized by MSO definable origin graphs into a tensor embedding

Keywords: transductions, tensor, origin graphs, strong capacity, regular functions

How to Cite:

Sun, Z. & Rawski, J., (2024) “Tensor Product Representations of Regular Transductions”, Society for Computation in Linguistics 7(1), 1–9. doi: https://doi.org/10.7275/scil.2124

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Published on
24 Jun 2024
Peer Reviewed