Paper Citation Record · LEDGER

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods

As of 12 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2601.23084.

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

pith.paper-citation-record.v1
2601.23084 v3

Coverage vector

measured 41 of 41 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-03T06:28:30.958930Z

measured 41 of 41 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

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Reference resolution

41 of 41 outbound references displayed

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Outbound references

Observation 4b138a1b-7c7f-4202-b126-9a3594cccd5a · outbound

This paper cites An introduction to quantum machine learning.Contemporary Physics, 56(2):172–185, 2015.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods An introduction to quantum machine learning.Contemporary Physics, 56(2):172–185, 2015

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:27.105827Z

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Unavailable: canonical work link unavailable.

Observation c1a2e7eb-2743-44d1-9e8e-40409c37acb7 · outbound

This paper cites Pac-bayes & margins.Advances in neural information pro- cessing systems, 15, 2002.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Pac-bayes & margins.Advances in neural information pro- cessing systems, 15, 2002

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:27.210966Z

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Observation 59af8a92-2f66-4317-983a-c61899e8dfc3 · outbound

This paper cites A pac-bayesian margin bound for linear classifiers: Why svms work.Advances in neural information processing systems, 13, 2000.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods A pac-bayesian margin bound for linear classifiers: Why svms work.Advances in neural information processing systems, 13, 2000

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:27.392835Z

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Observation aafef722-dc88-402c-9bd8-d06ae3e8fa9c · outbound

This paper cites Simplified pac-bayesian margin bounds.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Simplified pac-bayesian margin bounds

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:27.567171Z

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Observation 5fd0f548-7a56-4845-8e23-35e968d25436 · outbound

This paper cites an unresolved cited work.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:27.671816Z

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Observation bd80c8e1-cd2e-4949-ac18-51387a2f2585 · outbound

This paper cites Near-tight margin-based generalization bounds for support vector machines.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Near-tight margin-based generalization bounds for support vector machines

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:27.741759Z

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Observation e663c2dc-6f16-4f9f-8046-3babdd7b4837 · outbound

This paper cites Generaliza- tion performance of support vector machines and other pattern classifiers.Advances in Kernel meth- ods—support vector learning, pages 43–54, 1999.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Generaliza- tion performance of support vector machines and other pattern classifiers.Advances in Kernel meth- ods—support vector learning, pages 43–54, 1999

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:27.845745Z

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Observation 23335d0c-c175-4fbf-a06e-96d6412533fc · outbound

This paper cites On the uniform convergence of relative frequencies of events to their probabilities.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods On the uniform convergence of relative frequencies of events to their probabilities

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:27.914304Z

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Observation 87ed36a8-9b34-4753-90d4-22509a0c9857 · outbound

This paper cites Bounds on error expectation for support vector machines.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Bounds on error expectation for support vector machines

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:27.986521Z

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Observation 700318ad-0cea-47a7-b74b-9e00b89a3793 · outbound

This paper cites Springer Science & Business Media, 2006.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Springer Science & Business Media, 2006

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.053060Z

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Observation 7a14137c-dbc8-4c8e-8848-03720524357c · outbound

This paper cites Support- vector networks.Machine learning, 20(3):273– 297, 1995.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Support- vector networks.Machine learning, 20(3):273– 297, 1995

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.133585Z

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Observation d3cb7383-5b81-4a8a-a9d9-230af499b543 · outbound

This paper cites Quantum computing in the nisq era and beyond.Quantum, 2:79, 2018.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Quantum computing in the nisq era and beyond.Quantum, 2:79, 2018

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.271439Z

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Observation 6dc4bf17-2820-4a5b-afd8-f2a8b22473a5 · outbound

This paper cites Generalization in quantum machine learning from few training data.Nature communications, 13(1):4919, 2022.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Generalization in quantum machine learning from few training data.Nature communications, 13(1):4919, 2022

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.318247Z

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Observation ba15633a-9775-43bb-9968-2d3a1b185505 · outbound

This paper cites Understanding quantum machine learn- ing also requires rethinking generalization.Nature Communications, 15(1):2277, 2024.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Understanding quantum machine learn- ing also requires rethinking generalization.Nature Communications, 15(1):2277, 2024

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.385180Z

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Observation 705dca62-8da8-4854-a63b-5b5cd4b348bc · outbound

This paper cites Understanding gen- eralization in quantum machine learning with mar- gins.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Understanding gen- eralization in quantum machine learning with mar- gins

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.494211Z

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Observation 9afdf153-c8e8-476a-9563-9b056d667120 · outbound

This paper cites Towards understanding the power of quantum kernels in the nisq era.Quantum, 5: 531, 2021.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Towards understanding the power of quantum kernels in the nisq era.Quantum, 5: 531, 2021

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.615564Z

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Observation 0a1621d5-328e-4e45-aecc-61440c41a669 · outbound

This paper cites Power characterization of noisy quan- tum kernels.IEEE Transactions on Neural Net- works and Learning Systems, 2025.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Power characterization of noisy quan- tum kernels.IEEE Transactions on Neural Net- works and Learning Systems, 2025

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.719660Z

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Observation 251c9ab4-02a7-40f7-8f1d-721aa15a3ce5 · outbound

This paper cites Generalization error bound for quantum machine learning in nisq era—a survey.Quantum Machine Intelligence, 6(2):90, 2024.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Generalization error bound for quantum machine learning in nisq era—a survey.Quantum Machine Intelligence, 6(2):90, 2024

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.846388Z

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Observation a8b2951b-6145-49db-83b6-00acb7eddd18 · outbound

This paper cites Cambridge university press, 2010.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Cambridge university press, 2010

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:28.990174Z

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Observation 7b4ea8c9-e4aa-4dc8-9dc7-79e51ecaa2cb · outbound

This paper cites Rademacher and gaussian complexities: Risk bounds and structural results.Journal of Machine Learning Research, 3(Nov):463–482, 2002.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Rademacher and gaussian complexities: Risk bounds and structural results.Journal of Machine Learning Research, 3(Nov):463–482, 2002

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.136831Z

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Observation 72e299a8-d5ca-49e1-8c69-2fc28664fa40 · outbound

This paper cites Pseudo- dimension of quantum circuits.Quantum Machine Intelligence, 2(2):14, 2020.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Pseudo- dimension of quantum circuits.Quantum Machine Intelligence, 2(2):14, 2020

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.211542Z

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Observation b951efbe-78d9-4bc5-9374-4f5f4d118b70 · outbound

This paper cites Generalization in quantum machine learn- ing: A quantum information standpoint.PRX Quan- tum, 2(4):040321, 2021.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Generalization in quantum machine learn- ing: A quantum information standpoint.PRX Quan- tum, 2(4):040321, 2021

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.285581Z

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Observation 9aee3979-a770-4795-8f9b-8a89ac3b6dd8 · outbound

This paper cites an unresolved cited work.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Unresolved cited work

Reference 23

Resolution: malformed identifier; no resolver link, observed 2026-08-03T06:28:29.355201Z

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Observation e7405823-c14b-45e2-9cc6-af6294b018ce · outbound

This paper cites Statistical complexity of quan- tum circuits.Physical Review A, 105(6):062431, 2022.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Statistical complexity of quan- tum circuits.Physical Review A, 105(6):062431, 2022

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.439798Z

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Observation 1ee94349-798d-4760-9740-2256df6eed1f · outbound

This paper cites Effects of quantum resources and noise on the statistical complexity of quantum circuits.Quantum Science and Technology, 8(2): 025013, 2023.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Effects of quantum resources and noise on the statistical complexity of quantum circuits.Quantum Science and Technology, 8(2): 025013, 2023

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.518261Z

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Observation 67686a57-4588-462f-8dfd-49036510c994 · outbound

This paper cites Rademacher complexity of noisy quantum circuits.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Rademacher complexity of noisy quantum circuits

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.585309Z

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Observation 6d144beb-61c2-41b6-9998-52792f77f2ce · outbound

This paper cites Understanding deep learning (still) requires rethinking generaliza- tion.Communications of the ACM, 64(3):107–115, 2021.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Understanding deep learning (still) requires rethinking generaliza- tion.Communications of the ACM, 64(3):107–115, 2021

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.664076Z

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Observation eb996d3e-131e-4cc2-929c-27798be7bf82 · outbound

This paper cites Spectrally-normalized margin bounds for neural networks.Advances in neural information processing systems, 30, 2017.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Spectrally-normalized margin bounds for neural networks.Advances in neural information processing systems, 30, 2017

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.733788Z

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Observation 11634f85-82ce-4c9a-9aa6-3d0abb28fb3b · outbound

This paper cites Exponential concentration in quantum kernel methods.Nature communications, 15(1):5200, 2024.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Exponential concentration in quantum kernel methods.Nature communications, 15(1):5200, 2024

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.812419Z

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Observation dbef668d-3b53-4a74-a341-8310aab390a4 · outbound

This paper cites A training algorithm for optimal margin classifiers.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods A training algorithm for optimal margin classifiers

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.883714Z

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Observation 4d96863d-fbcc-4718-abfc-08da77c44ae2 · outbound

This paper cites Quantum ma- chine learning in feature hilbert spaces.Physical review letters, 122(4):040504, 2019.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Quantum ma- chine learning in feature hilbert spaces.Physical review letters, 122(4):040504, 2019

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:29.942329Z

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Observation 95b0fbf8-a015-47c0-87d8-86d4db46ce17 · outbound

This paper cites an unresolved cited work.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Unresolved cited work

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.035029Z

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Observation a9a75056-91b4-4af8-bd94-af12d4e96264 · outbound

This paper cites Supervised learning with quantum-enhanced feature spaces.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Supervised learning with quantum-enhanced feature spaces

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.114763Z

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Observation d611ab11-aa38-464d-8d7a-4409f58d3c7b · outbound

This paper cites Cross-validation., 2019.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Cross-validation., 2019

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.223266Z

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Observation 68ef189b-7b09-49ed-b2be-007c31601ee4 · outbound

This paper cites Principal component analysis.Chemometrics and intelligent laboratory systems, 2(1-3):37–52, 1987.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Principal component analysis.Chemometrics and intelligent laboratory systems, 2(1-3):37–52, 1987

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.280645Z

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Observation 6f9a4610-55f5-4674-af7e-9cf1a161e8a2 · outbound

This paper cites Learnability of quan- tum neural networks.PRX quantum, 2(4):040337, 2021.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Learnability of quan- tum neural networks.PRX quantum, 2(4):040337, 2021

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.379225Z

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Observation 0e17e6e2-5f34-4cc3-b7f7-a9d46670c90e · outbound

This paper cites K-fold cross validation for error rate estimate in support vector machines.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods K-fold cross validation for error rate estimate in support vector machines

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.581978Z

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Observation 45604f51-5de2-4c19-ac38-13af3fb4c0db · outbound

This paper cites PennyLane: Automatic differentiation of hybrid quantum-classical computations.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods PennyLane: Automatic differentiation of hybrid quantum-classical computations

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.690237Z

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Observation 79e9e9f0-4af2-4aeb-81c3-5aca18a2f8f3 · outbound

This paper cites Wood, Jake Lishman, Julien Gacon, Simon Martiel, Paul D.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods Wood, Jake Lishman, Julien Gacon, Simon Martiel, Paul D

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.786776Z

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Observation 463dcd96-ca6e-42a3-bf07-4fcf1ed950e5 · outbound

This paper cites com/, 2025.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods com/, 2025

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.854107Z

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Observation c54719b6-d2c1-4bfb-a072-5385a80b15d2 · outbound

This paper cites M" or "B.

The Cross-Kernel Margin: A Robustness Measure for Quantum Kernel Methods M" or "B

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T06:28:30.958930Z

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Pith citing papers

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