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We provide conceptual and mathematical foundations for near-term quantum natural language processing (QNLP), and do so in quantum computer scientist friendly terms.
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Quantum links let computers read
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Mathematical foundations for a compositional distributional model of meaning
B. Coecke, M. Sadrzadeh, and S. Clark · 2010
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Knowledge graph completion via complex tensor factorization
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Towards compositional distributional discourse analysis
B. Coecke, G. De Felice, D. Marsden, and A. Toumi · 2018
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Modelling lexical ambiguity with density matrices
F. Meyer and M. Lewis · 2010
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Interacting quantum observables: categorical algebra and diagrammatics
B. Coecke and R. Duncan · 2011
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Categories for the practicing physicist
B. Coecke and É. O. Paquette · 2011
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Experimental support for a categorical compositional distributional model of meaning
E. Grefenstette and M. Sadrzadeh · 2011
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A survey of graphical languages for monoidal categories
P. Selinger · 2011
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Picturing classical and quantum bayesian inference
B. Coecke and R. W. Spekkens · 2012
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J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2018
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Two complete axiomatisations of pure-state qubit quantum computing
A. Hadzihasanovic, K. F. Ng, and Q. Wang · 2018
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The book of why: the new science of cause and effect
J. Pearl and D. Mackenzie · 2018
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Categorical compositional distributional questions, answers & discourse analysis
A. Toumi · 2018
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A near-optimal axiomatisation of zx-calculus for pure qubit quantum mechanics
R. Vilmart · 2018
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Qutrit zx-calculus is complete for stabilizer quantum mechanics
Q. Wang · 2018
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Graded hyponymy for compositional distributional semantics
D. Bankova, B. Coecke, M. Lewis, and D. Marsden · 2019
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A quantum search decoder for natural language processing
J. Bausch, S. Subramanian, and S. Piddock · 2019
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Parameterized quantum circuits as machine learning models
M. Benedetti, E. Lloyd, S. Sack, and M. Fiorentini · 2019
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On the measure of intelligence
F. Chollet · 2019
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G. de Felice, K. Meichanetzidis, and A. Toumi · 2019
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Autonomization of monoidal categories
A. Delpeuch · 2019
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Graph-theoretic simplification of quantum circuits with the zx-calculus
R. Duncan, A. Kissinger, S. Pedrix, and J. van de Wetering · 2019
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Pyzx: Large scale automated diagrammatic reasoning
A. Kissinger and J. van de Wetering · 2019
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Reducing t-count with the zx-calculus
A. Kissinger and J. van de Wetering · 2019
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Compositional hyponymy with positive operators
M. Lewis · 2019
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Towards negation in discocat, 2019
M. Lewis · 2019
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Variational quantum circuit model for knowledge graph embedding
Y. Ma, V. Tresp, L. Zhao, and Y. Wang · 2019
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N. Wiebe, A. Bocharov, P. Smolensky, M. Troyer, and K. M. Svore · 2019
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Evaluating composition models for verb phrase elliptical sentence embeddings
G. Wijnholds and M. Sadrzadeh · 2019
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Language models are few-shot learners
T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al · 2020
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Quantum natural language processing. we did it! on an actual quantum computer!, April 2020
B. Coecke, G. de Felice, K. Meichanetzidis, and A. Toumi · 2020
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Meaning updating of density matrices
B. Coecke and K. Meichanetzidis · 2020
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De-humanising grammar for improved machine use
B. Coecke and V. Wang · 2020
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Cats climb entails mammals move: preserving hyponymy in compositional distributional semantics
G. De las Cuevas, A. Klingler, M. Lewis, and T. Netzer · 2020
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Classical and quantum algorithms for tensor principal component analysis
M. B. Hastings · 2020
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A rigorous and robust quantum speed-up in supervised machine learning
Y. Liu, S. Arunachalam, and K. Temme · 2020
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Quantum algorithms for nlp: Lsa, qsfa and ca
A. Luongo and A. Bellante · 2020
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Grammar-aware question-answering on quantum computers
K. Meichanetzidis, A. Toumi, G. de Felice, and B. Coecke · 2020
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Circuit-centric quantum classifiers
M. Schuld, A. Bocharov, and N. Svore, K. M.and Wiebe · 2020
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t | | ket > > : A retargetable compiler for NISQ devices
S. Sivarajah, S. Dilkes, A. Cowtan, W. Simmons, A. Edgington, and R. Duncan · 2020
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On the quantum versus classical learnability of discrete distributions
R. Sweke, J.-P. Seifert, D. Hangleiter, and J. Eisert · 2020
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Representation learning for type-driven composition
G. Wijnholds, M. Sadrzadeh, and S. Clark · 2020
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