Compositionality as we see it, everywhere around us
Not on the map. Why?
Abstract (arXiv)
There are different meanings of the term "compositionality" within science: what one researcher would call compositional, is not at all compositional for another researcher. The most established conception is usually attributed to Frege, and is characterised by a bottom-up flow of meanings: the meaning of the whole can be derived from the meanings of the parts, and how these parts are structured together. Inspired by work on compositionality in quantum theory, and categorical quantum mechanics in particular, we propose the notions of Schrodinger, Whitehead, and complete compositionality. Accounting for recent important developments in quantum technology and artificial intelligence, these do not have the bottom-up meaning flow as part of their definitions. Schrodinger compositionality accommodates quantum theory, and also meaning-as-context. Complete compositionality further strengthens Schrodinger compositionality in order to single out theories like ZX-calculus, that are complete with regard to the intended model. All together, our new notions aim to capture the fact that compositionality is at its best when it is `real', `non-trivial', and even more when it also is `complete'. At this point we only put forward the intuitive and/or restricted formal definitions, and leave a fully comprehensive definition to future collaborative work.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 22 of its 116 references that are in the map. First posted on arXiv 11 Oct 2021.
Builds on
22 of 116 references.
References · 22
- 2021QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computercited by 67
- 2020Foundations for Near-Term Quantum Natural Language Processingcited by 51
- 2021lambeq: An Efficient High-Level Python Library for Quantum NLPcited by 44
- 2020Quantum Natural Language Processing on Near-Term Quantum Computerscited by 39
- 2021Category Theory in Machine Learningcited by 36
- 2014The Frobenius anatomy of word meanings I: subject and object relative pronounscited by 24
- 2016Quantum Algorithms for Compositional Natural Language Processingcited by 24
- 2019The Mathematics of Text Structurecited by 24
- 2019Graph-theoretic Simplification of Quantum Circuits with the ZX-calculuscited by 20
- 2015Open System Categorical Quantum Semantics in Natural Language Processingcited by 17
- 2016Compositional game theorycited by 13
- 2017Interacting Conceptual Spaces I : Grammatical Composition of Conceptscited by 13
10 more
- 2020Meaning updating of density matricescited by 9
- 2021Grammar Equationscited by 7
- 2021How to make qubits speakcited by 5
- 2013A quantum teleportation inspired algorithm produces sentence meaning from word meaning and grammatical structurecited by 4
- 2015A Diagrammatic Axiomatisation for Qubit Entanglementcited by 4
- 2017The ZX calculus is a language for surface code lattice surgerycited by 4
- 2021Kindergarden quantum mechanics graduates (...or how I learned to stop gluing LEGO together and love the ZX-calculus)cited by 4
- 2021Talking Space: inference from spatial linguistic meaningscited by 4
- 2017A categorical semantics for causal structurecited by 3
- 2016From quantum foundations via natural language meaning to a theory of everythingcited by 2
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 2; 2025: 3; 2026: 3.
11 papers.
- 2024Towards Compositional Interpretability for XAIcited by 12
- 2021A Quantum Natural Language Processing Approach to Musical Intelligencecited by 11
- 2023Distilling Text into Circuitscited by 7
- 2025Compositionality Unlocks Deep Interpretable Modelscited by 6
- 2022Categorical semantics of compositional reinforcement learningcited by 5
- 2025Finding Manifolds With Bilinear Autoencoderscited by 5
- 2024Quantum Algorithms for Compositional Text Processingcited by 3
- 2026Bilinear autoencoders find interpretable manifoldscited by 1
- 2026From Mechanistic to Compositional Interpretabilitycited by 1
- 2025Causal Models for Growing Networkscited by 0
- 2026Categorical AI phenomenology: A first-person approachcited by 0
- 2026Categorical AI phenomenology: A first-person approach19 Aug 2026
- 2026From Mechanistic to Compositional Interpretability9 May 2026
- 2026Bilinear autoencoders find interpretable manifolds9 May 2026
- 2025Finding Manifolds With Bilinear Autoencoders19 Oct 2025
- 2025Compositionality Unlocks Deep Interpretable Models3 Apr 2025
- 2025Causal Models for Growing Networks1 Apr 2025
- 2024Quantum Algorithms for Compositional Text Processing12 Aug 2024
- 2024Towards Compositional Interpretability for XAI25 Jun 2024
- 2023Distilling Text into Circuits25 Jan 2023
- 2022Categorical semantics of compositional reinforcement learning29 Aug 2022
- 2021A Quantum Natural Language Processing Approach to Musical Intelligence10 Nov 2021