Paper Citation Record · LEDGER

Learning Complex Word Embeddings in Classical and Quantum Spaces

As of 14 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2412.13745.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.13745 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

50 of 50 outbound references displayed

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External citation measurements

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Outbound references

Observation 11bc3f8e-a4db-4353-8acc-df74dd6e8640 · outbound

This paper cites A study on similarity and relatedness using distributional and W ord N et-based approaches.

Learning Complex Word Embeddings in Classical and Quantum Spaces A study on similarity and relatedness using distributional and W ord N et-based approaches

Reference 1

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Learning Complex Word Embeddings in Classical and Quantum Spaces Quantum Computing since Democritus

Reference 2

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This paper cites Huggins, Ramis Movassagh, Dar Gilboa, and Jarrod McClean.

Learning Complex Word Embeddings in Classical and Quantum Spaces Huggins, Ramis Movassagh, Dar Gilboa, and Jarrod McClean

Reference 3

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Learning Complex Word Embeddings in Classical and Quantum Spaces Unitary evolution recurrent neural networks

Reference 4

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Learning Complex Word Embeddings in Classical and Quantum Spaces Recurrent quantum neural networks

Reference 5

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Learning Complex Word Embeddings in Classical and Quantum Spaces Bankova, B

Reference 6

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Learning Complex Word Embeddings in Classical and Quantum Spaces Quantum fingerprinting

Reference 7

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Learning Complex Word Embeddings in Classical and Quantum Spaces A quantum-theoretic approach to distributional semantics

Reference 8

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Learning Complex Word Embeddings in Classical and Quantum Spaces Parameterized quantum circuits as machine learning models

Reference 9

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Learning Complex Word Embeddings in Classical and Quantum Spaces Vector space models of lexical meaning

Reference 10

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This paper cites Mathematical foundations for a compositional distributional model of meaning.

Learning Complex Word Embeddings in Classical and Quantum Spaces Mathematical foundations for a compositional distributional model of meaning

Reference 11

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Observation d1fbcc8c-4055-4496-9218-b487c10382e3 · outbound

This paper cites Scalable and interpretable quantum natural language processing: an implementation on trapped ions.

Learning Complex Word Embeddings in Classical and Quantum Spaces Scalable and interpretable quantum natural language processing: an implementation on trapped ions

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Learning Complex Word Embeddings in Classical and Quantum Spaces Demonstration of logical qubits and repeated error correction with better-than-physical error rates

Reference 13

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Learning Complex Word Embeddings in Classical and Quantum Spaces Unresolved cited work

Reference 14

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Learning Complex Word Embeddings in Classical and Quantum Spaces The Geometry of Meaning

Reference 15

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Learning Complex Word Embeddings in Classical and Quantum Spaces Noise-contrastive estimation: A new estimation principle for unnormalized statistical models

Reference 16

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Observation 65a5b45c-327d-4055-9adc-528ae02b63d5 · outbound

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Learning Complex Word Embeddings in Classical and Quantum Spaces Georgiou and C

Reference 17

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Learning Complex Word Embeddings in Classical and Quantum Spaces Quantum linear algebra is all you need for transformer architectures

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Learning Complex Word Embeddings in Classical and Quantum Spaces Unresolved cited work

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Learning Complex Word Embeddings in Classical and Quantum Spaces Birgitta Whaley, and E

Reference 20

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Learning Complex Word Embeddings in Classical and Quantum Spaces Long Short-Term Memory

Reference 21

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Learning Complex Word Embeddings in Classical and Quantum Spaces Improving word representations via global context and multiple word prototypes

Reference 22

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Learning Complex Word Embeddings in Classical and Quantum Spaces Sequence Processing with Quantum Tensor Networks

Reference 23

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Learning Complex Word Embeddings in Classical and Quantum Spaces Quixer: A Quantum Transformer Model

Reference 24

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Learning Complex Word Embeddings in Classical and Quantum Spaces Towards logical negation for compositional distributional semantics

Reference 25

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Learning Complex Word Embeddings in Classical and Quantum Spaces QNLP in practice: Running compositional models of meaning on a quantum computer

Reference 26

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Learning Complex Word Embeddings in Classical and Quantum Spaces Barren Plateaus in Variational Quantum Computing

Reference 27

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Learning Complex Word Embeddings in Classical and Quantum Spaces Quantum-inspired complex word embedding

Reference 28

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Learning Complex Word Embeddings in Classical and Quantum Spaces Unresolved cited work

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Learning Complex Word Embeddings in Classical and Quantum Spaces McClean, Sergio Boixo, Vadim N

Reference 30

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Learning Complex Word Embeddings in Classical and Quantum Spaces Efficient estimation of word representations in vector space

Reference 31

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Learning Complex Word Embeddings in Classical and Quantum Spaces Distributed representations of words and phrases and their compositionality

Reference 32

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Learning Complex Word Embeddings in Classical and Quantum Spaces Nielsen and Isaac L

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Learning Complex Word Embeddings in Classical and Quantum Spaces Poincare embeddings for learning hierarchical representations

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Learning Complex Word Embeddings in Classical and Quantum Spaces Peruzzo, J

Reference 35

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Learning Complex Word Embeddings in Classical and Quantum Spaces Quantum C omputing in the NISQ era and beyond

Reference 36

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Learning Complex Word Embeddings in Classical and Quantum Spaces G lo V e: Global vectors for word representation

Reference 37

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Learning Complex Word Embeddings in Classical and Quantum Spaces Conversational negation using worldly context in compositional distributional semantics

Reference 38

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Learning Complex Word Embeddings in Classical and Quantum Spaces Johnson, and Alan Aspuru-Guzik

Reference 39

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Learning Complex Word Embeddings in Classical and Quantum Spaces Modeling term dependencies with quantum language models for IR

Reference 40

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Learning Complex Word Embeddings in Classical and Quantum Spaces Supervised learning with tensor networks

Reference 41

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Learning Complex Word Embeddings in Classical and Quantum Spaces Unresolved cited work

Reference 42

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Learning Complex Word Embeddings in Classical and Quantum Spaces Shaikh, Sara Sabrina Zemljic, and Stephen Clark

Reference 43

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Learning Complex Word Embeddings in Classical and Quantum Spaces The Geometry of Information Retrieval

Reference 44

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Learning Complex Word Embeddings in Classical and Quantum Spaces Attention is all you need

Reference 45

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Learning Complex Word Embeddings in Classical and Quantum Spaces Quantum Natural Language Processing

Reference 46

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Learning Complex Word Embeddings in Classical and Quantum Spaces Orthogonal negation in vector spaces for modelling word-meanings and document retrieval

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:53:51.529428Z

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This paper cites Natural language processing meets quantum physics: A survey and categorization.

Learning Complex Word Embeddings in Classical and Quantum Spaces Natural language processing meets quantum physics: A survey and categorization

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:53:51.517389Z

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Learning Complex Word Embeddings in Classical and Quantum Spaces Quantum recurrent architectures for text classification

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:53:51.504264Z

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This paper cites Quantum state preparation with optimal circuit depth: Implementations and applications.

Learning Complex Word Embeddings in Classical and Quantum Spaces Quantum state preparation with optimal circuit depth: Implementations and applications

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:53:51.491291Z

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Pith citing papers

No inbound Pith citation observations are available.