Paper Citation Record · LEDGER

Learning to Program Quantum Measurements for Machine Learning

As of 19 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2505.13525.

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

pith.paper-citation-record.v1
2505.13525 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:42:59.387753Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:16:41.534509Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T14:16:42.028371Z

Reference resolution

52 of 52 outbound references displayed

verified exact0
verified fuzzy7
unresolved45
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0f1e0777-e7b5-462a-9c8e-13ace4ea05a9 · outbound

This paper cites an unresolved cited work.

Learning to Program Quantum Measurements for Machine Learning Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.189615Z

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Observation 4a31ce38-00c7-41f5-a6ec-fc2d4c68bda9 · outbound

This paper cites Mastering the game of go without human knowledge,.

Learning to Program Quantum Measurements for Machine Learning Mastering the game of go without human knowledge,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.194430Z

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Observation 690bf741-bf5e-46ad-a4ba-d332b89067ff · outbound

This paper cites Attention is all you need,.

Learning to Program Quantum Measurements for Machine Learning Attention is all you need,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.198681Z

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Observation 0e920dcd-53ff-4dbe-9e5c-a6bbfa0d24c0 · outbound

This paper cites Noisy intermediate-scale quantum algorithms,.

Learning to Program Quantum Measurements for Machine Learning Noisy intermediate-scale quantum algorithms,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.202909Z

Source-reported events for the cited work

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Observation 6c4457da-7710-4829-9921-23a7d250866c · outbound

This paper cites Variational quantum algorithms,.

Learning to Program Quantum Measurements for Machine Learning Variational quantum algorithms,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.207083Z

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Observation 3b5a150a-459c-4457-a9d7-60e15d8cd68c · outbound

This paper cites A variational eigenvalue solver on a photonic quantum processor,.

Learning to Program Quantum Measurements for Machine Learning A variational eigenvalue solver on a photonic quantum processor,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.211200Z

Source-reported events for the cited work

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Observation ea8442a9-39bb-4ef0-915c-91b0b2975eb2 · outbound

This paper cites A Quantum Approximate Optimization Algorithm.

Learning to Program Quantum Measurements for Machine Learning A Quantum Approximate Optimization Algorithm

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.215446Z

Source-reported events for the cited work

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Observation e9227940-b29b-4efd-9f6e-4673e488076f · outbound

This paper cites Quantum circuit learning,.

Learning to Program Quantum Measurements for Machine Learning Quantum circuit learning,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.219440Z

Source-reported events for the cited work

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Observation 17231cd6-07db-47c3-a91d-2e4d0eda1c89 · outbound

This paper cites Circuit-centric quantum classifiers,.

Learning to Program Quantum Measurements for Machine Learning Circuit-centric quantum classifiers,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.223156Z

Source-reported events for the cited work

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Observation a5317ea1-bb10-4ce4-ac4e-e207c5474ccf · outbound

This paper cites An end-to- end trainable hybrid classical-quantum classifier,.

Learning to Program Quantum Measurements for Machine Learning An end-to- end trainable hybrid classical-quantum classifier,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.226865Z

Source-reported events for the cited work

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Observation 2722b064-7b27-4433-a66a-e71d011ec31a · outbound

This paper cites Quantum convolutional neural networks for high energy physics data analysis,.

Learning to Program Quantum Measurements for Machine Learning Quantum convolutional neural networks for high energy physics data analysis,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.230688Z

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Observation a1e49079-f70e-4dda-88b9-a31265a3a0e5 · outbound

This paper cites Qtn-vqc: An end-to-end learning framework for quantum neural networks,.

Learning to Program Quantum Measurements for Machine Learning Qtn-vqc: An end-to-end learning framework for quantum neural networks,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.234973Z

Source-reported events for the cited work

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Observation 78c25c41-f841-40ab-9e8f-f10c110e6092 · outbound

This paper cites Quantum gradient class activation map for model interpretability,.

Learning to Program Quantum Measurements for Machine Learning Quantum gradient class activation map for model interpretability,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.238524Z

Source-reported events for the cited work

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Observation 760e2523-dcd2-404c-9cac-207cfb3fb606 · outbound

This paper cites Quantum long short-term memory,.

Learning to Program Quantum Measurements for Machine Learning Quantum long short-term memory,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.242028Z

Source-reported events for the cited work

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Observation 6c9c14e3-40bf-4af1-a336-ab97c626e6a4 · outbound

This paper cites Qeegnet: Quantum machine learning for enhanced electroencephalography en- coding,.

Learning to Program Quantum Measurements for Machine Learning Qeegnet: Quantum machine learning for enhanced electroencephalography en- coding,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:59.879554Z

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Observation b11a5808-1dfb-4e8c-bbc3-e0edfadc1761 · outbound

This paper cites Iqgan: Robust quantum generative adversarial network for image synthesis on nisq devices,.

Learning to Program Quantum Measurements for Machine Learning Iqgan: Robust quantum generative adversarial network for image synthesis on nisq devices,

Reference 16

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Source-reported events for the cited work

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Observation f38d962e-e1ef-44f2-aeeb-11ba7a6c690b · outbound

This paper cites Pqlm-multilingual decentralized portable quantum language model,.

Learning to Program Quantum Measurements for Machine Learning Pqlm-multilingual decentralized portable quantum language model,

Reference 17

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Source-reported events for the cited work

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Observation 25c188e4-7a61-4302-8c98-fbb8278aaec1 · outbound

This paper cites When bert meets quantum temporal convolution learning for text classification in heterogeneous computing,.

Learning to Program Quantum Measurements for Machine Learning When bert meets quantum temporal convolution learning for text classification in heterogeneous computing,

Reference 18

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Source-reported events for the cited work

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Observation 3696cdeb-f6b6-43b1-b25c-5e186e0cfd20 · outbound

This paper cites The dawn of quantum natural language processing,.

Learning to Program Quantum Measurements for Machine Learning The dawn of quantum natural language processing,

Reference 19

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Observation 74f8a119-bd96-492b-8327-15531b3e9d00 · outbound

This paper cites Applying qnlp to sentiment analysis in finance,.

Learning to Program Quantum Measurements for Machine Learning Applying qnlp to sentiment analysis in finance,

Reference 20

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Source-reported events for the cited work

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Observation 07913f94-13ce-454f-a46d-f46549bd1141 · outbound

This paper cites Quantum-Train: Rethinking Hybrid Quantum-Classical Machine Learning in the Model Compression Perspective.

Learning to Program Quantum Measurements for Machine Learning Quantum-Train: Rethinking Hybrid Quantum-Classical Machine Learning in the Model Compression Perspective

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.267824Z

Source-reported events for the cited work

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Observation 02ad7505-00c3-4750-9f7f-33a9993c7812 · outbound

This paper cites Quantum-Train Long Short-Term Memory: Application on Flood Prediction Problem.

Learning to Program Quantum Measurements for Machine Learning Quantum-Train Long Short-Term Memory: Application on Flood Prediction Problem

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.272298Z

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Observation db57d4fb-92e4-4962-a33f-13fe7954fdec · outbound

This paper cites QTRL: Toward Practical Quantum Reinforcement Learning via Quantum-Train.

Learning to Program Quantum Measurements for Machine Learning QTRL: Toward Practical Quantum Reinforcement Learning via Quantum-Train

Reference 23

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Observation 68a75ec8-af11-48d7-8409-e3d46ea5516b · outbound

This paper cites Federated Quantum-Train with Batched Parameter Generation.

Learning to Program Quantum Measurements for Machine Learning Federated Quantum-Train with Batched Parameter Generation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.280587Z

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Observation 10818272-262d-40ff-9aa9-0bc2dcbcf789 · outbound

This paper cites Quantum-Train with Tensor Network Mapping Model and Distributed Circuit Ansatz.

Learning to Program Quantum Measurements for Machine Learning Quantum-Train with Tensor Network Mapping Model and Distributed Circuit Ansatz

Reference 25

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Source-reported events for the cited work

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Observation effc9bc1-dce4-4195-af96-ef04e9a96f71 · outbound

This paper cites Quantum-Trained Convolutional Neural Network for Deepfake Audio Detection.

Learning to Program Quantum Measurements for Machine Learning Quantum-Trained Convolutional Neural Network for Deepfake Audio Detection

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.288675Z

Source-reported events for the cited work

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Observation 70cb37f8-2303-4f2b-92b0-62ae162278c7 · outbound

This paper cites A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning.

Learning to Program Quantum Measurements for Machine Learning A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning

Reference 27

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Observation 4b94b6d0-3d01-4e95-aa0c-14c641473a49 · outbound

This paper cites Quantum-Train-Based Distributed Multi-Agent Reinforcement Learning.

Learning to Program Quantum Measurements for Machine Learning Quantum-Train-Based Distributed Multi-Agent Reinforcement Learning

Reference 28

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Observation c17278f3-14ed-4bd4-ba4d-8a8675ba5f8b · outbound

This paper cites Programming Variational Quantum Circuits with Quantum-Train Agent.

Learning to Program Quantum Measurements for Machine Learning Programming Variational Quantum Circuits with Quantum-Train Agent

Reference 29

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Observation 7ff6c74f-ae01-4ba0-b9e0-e78278f25dc8 · outbound

This paper cites Variational quantum reinforcement learning via evolutionary optimiza- tion,.

Learning to Program Quantum Measurements for Machine Learning Variational quantum reinforcement learning via evolutionary optimiza- tion,

Reference 30

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Observation 9dad7928-7139-41fd-b9fe-4edcd039cb4f · outbound

This paper cites Variational quantum circuits for deep reinforcement learning,.

Learning to Program Quantum Measurements for Machine Learning Variational quantum circuits for deep reinforcement learning,

Reference 31

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Observation aac87b10-7062-41cd-b18b-69484605e3d2 · outbound

This paper cites Efficient quantum recurrent reinforcement learning via quantum reservoir computing,.

Learning to Program Quantum Measurements for Machine Learning Efficient quantum recurrent reinforcement learning via quantum reservoir computing,

Reference 32

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Observation f9da421e-9001-4598-94d5-7dceab7bc90f · outbound

This paper cites A Survey on Quantum Reinforcement Learning.

Learning to Program Quantum Measurements for Machine Learning A Survey on Quantum Reinforcement Learning

Reference 33

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Observation f12e8860-9e0c-4981-9589-770b2da60811 · outbound

This paper cites Quantum deep recurrent reinforcement learning,.

Learning to Program Quantum Measurements for Machine Learning Quantum deep recurrent reinforcement learning,

Reference 34

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Observation c1cb7517-53ce-4ee4-88b6-9b15ffebd9bc · outbound

This paper cites Reinforcement learning with quantum vari- ational circuit,.

Learning to Program Quantum Measurements for Machine Learning Reinforcement learning with quantum vari- ational circuit,

Reference 35

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Observation 6c874de0-eb54-4631-9382-44cbca3c14ad · outbound

This paper cites Quantum agents in the gym: a variational quantum algorithm for deep q-learning,.

Learning to Program Quantum Measurements for Machine Learning Quantum agents in the gym: a variational quantum algorithm for deep q-learning,

Reference 36

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Observation 0b6b7d37-c6ae-4fa9-9bb3-92d930feb392 · outbound

This paper cites Parametrized quantum policies for reinforcement learning,.

Learning to Program Quantum Measurements for Machine Learning Parametrized quantum policies for reinforcement learning,

Reference 37

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Observation d5d500cf-6b3c-4912-9475-b37303c0cb13 · outbound

This paper cites Vqc-based reinforcement learning with data re-uploading: performance and trainability,.

Learning to Program Quantum Measurements for Machine Learning Vqc-based reinforcement learning with data re-uploading: performance and trainability,

Reference 38

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Observation c20ff181-9e2b-4b9a-bde6-11e493ca0092 · outbound

This paper cites Asynchronous training of quantum reinforcement learning,.

Learning to Program Quantum Measurements for Machine Learning Asynchronous training of quantum reinforcement learning,

Reference 39

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Observation 60e90512-8379-4133-83f0-ac0b821b2d44 · outbound

This paper cites Quantum multi-agent meta reinforce- ment learning,.

Learning to Program Quantum Measurements for Machine Learning Quantum multi-agent meta reinforce- ment learning,

Reference 40

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Observation d5749e0e-1f2b-4215-8da5-ffcf2ddf5bba · outbound

This paper cites Learning to Measure Quantum Neural Networks.

Learning to Program Quantum Measurements for Machine Learning Learning to Measure Quantum Neural Networks

Reference 41

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Source-reported events for the cited work

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Observation 7451146c-f4fa-4eb5-adc6-76cb0814439e · outbound

This paper cites Quantum architecture search: a survey,.

Learning to Program Quantum Measurements for Machine Learning Quantum architecture search: a survey,

Reference 42

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Observation 943e7d6d-4c4e-48cf-932f-e53359fe1374 · outbound

This paper cites Differentiable quantum architecture search,.

Learning to Program Quantum Measurements for Machine Learning Differentiable quantum architecture search,

Reference 43

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Observation 051f7330-7d2a-4a76-9baf-cdf411e09bbf · outbound

This paper cites Differentiable quantum architecture search in asyn- chronous quantum reinforcement learning,.

Learning to Program Quantum Measurements for Machine Learning Differentiable quantum architecture search in asyn- chronous quantum reinforcement learning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:59.696918Z

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Observation 3aa2997e-35ad-4f12-b6f0-1cb24ace5d4f · outbound

This paper cites DARTS: Differentiable Architecture Search.

Learning to Program Quantum Measurements for Machine Learning DARTS: Differentiable Architecture Search

Reference 45

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Source-reported events for the cited work

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Observation ea817d8a-a521-4675-b981-c33b145fc0ae · outbound

This paper cites Learning to control fast-weight memories: An alterna- tive to dynamic recurrent networks,.

Learning to Program Quantum Measurements for Machine Learning Learning to control fast-weight memories: An alterna- tive to dynamic recurrent networks,

Reference 46

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Observation 9e0f7c2a-e34d-431f-9630-f6519602784e · outbound

This paper cites Learning to program variational quantum circuits with fast weights,.

Learning to Program Quantum Measurements for Machine Learning Learning to program variational quantum circuits with fast weights,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:59.672673Z

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Observation 634ce4b3-7b9f-4795-a93c-dcbb5544ae26 · outbound

This paper cites Nonlinear dimensionality reduction by locally linear embedding,.

Learning to Program Quantum Measurements for Machine Learning Nonlinear dimensionality reduction by locally linear embedding,

Reference 48

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Observation 31868c05-5ea6-4d30-9af8-4355e1def48d · outbound

This paper cites Laplacian eigenmaps for dimensionality reduction and data representation,.

Learning to Program Quantum Measurements for Machine Learning Laplacian eigenmaps for dimensionality reduction and data representation,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:59.376030Z

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Observation db1f294f-2341-4784-8891-005147537d1f · outbound

This paper cites Bleecker, Gauge theory and variational principles.

Learning to Program Quantum Measurements for Machine Learning Bleecker, Gauge theory and variational principles

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:59.639558Z

Source-reported events for the cited work

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Observation 4c08afe0-df6f-4af5-aa29-03f0a6da4d51 · outbound

This paper cites Gravitational Theories with Torsion.

Learning to Program Quantum Measurements for Machine Learning Gravitational Theories with Torsion

Reference 51

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Observation 3dab416b-5512-46c9-9498-1172b78ddd89 · outbound

This paper cites Jost and J.

Learning to Program Quantum Measurements for Machine Learning Jost and J

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:59.624130Z

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Pith citing papers

Observation 2ced6342-706c-4f52-9059-90fef937aaeb · inbound

Quantum Reinforcement Learning by Adaptive Non-local Observables cites this paper.

Quantum Reinforcement Learning by Adaptive Non-local Observables Learning to Program Quantum Measurements for Machine Learning

Reference 31

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Source-reported events for the cited work

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