Towards a Formal Distributional Semantics: Simulating Logical Calculi with Tensors
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Abstract (arXiv)
The development of compositional distributional models of semantics reconciling the empirical aspects of distributional semantics with the compositional aspects of formal semantics is a popular topic in the contemporary literature. This paper seeks to bring this reconciliation one step further by showing how the mathematical constructs commonly used in compositional distributional models, such as tensors and matrices, can be used to simulate different aspects of predicate logic. This paper discusses how the canonical isomorphism between tensors and multilinear maps can be exploited to simulate a full-blown quantifier-free predicate calculus using tensors. It provides tensor interpretations of the set of logical connectives required to model propositional calculi. It suggests a variant of these tensor calculi capable of modelling quantifiers, using few non-linear operations. It finally discusses the relation between these variants, and how this relation should constitute the subject of future work.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Apr 2013.
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Citing papers per year: 2021: 4; 2022: 1; 2023: 0; 2024: 4; 2025: 0; 2026: 1.
10 papers.
- 2021Logic Embeddings for Complex Query Answeringcited by 17
- 2021Learning Symbolic Rules for Reasoning in Quasi-Natural Languagecited by 9
- 2021Evaluating Relaxations of Logic for Neural Networks: A Comprehensive Studycited by 8
- 2022Understanding the Use of Quantifiers in Mandarincited by 3
- 2024Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network modelscited by 2
- 2024Boolean Matrix Logic Programming on the GPUcited by 1
- 2026A vector logic for intensional formal semanticscited by 1
- 2021Pregroup Grammars, their Syntax and Semanticscited by 0
- 2024Simulating Petri nets with Boolean Matrix Logic Programmingcited by 0
- 2024Active learning of digenic functions with boolean matrix logic programmingcited by 0
- 2026A vector logic for intensional formal semantics3 Feb 2026
- 2024Active learning of digenic functions with boolean matrix logic programming19 Aug 2024
- 2024Boolean Matrix Logic Programming on the GPU19 Aug 2024
- 2024Simulating Petri nets with Boolean Matrix Logic Programming18 May 2024
- 2024Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models10 May 2024
- 2022Understanding the Use of Quantifiers in Mandarin24 Sep 2022
- 2021Learning Symbolic Rules for Reasoning in Quasi-Natural Language23 Nov 2021
- 2021Pregroup Grammars, their Syntax and Semantics23 Sep 2021
- 2021Evaluating Relaxations of Logic for Neural Networks: A Comprehensive Study28 Jul 2021
- 2021Logic Embeddings for Complex Query Answering28 Feb 2021