Paper Citation Record · LEDGER

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool

As of 4 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2605.29877.

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

pith.paper-citation-record.v1
2605.29877 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T07:06:14.748337Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

verified exact3
verified fuzzy0
unresolved40
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 107da2e7-3dec-47ed-afff-2f3009013cb3 · outbound

This paper cites Quantum machine learning.Nature, 549(7671):195–202, 2017.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Quantum machine learning.Nature, 549(7671):195–202, 2017

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a0d29e8-af4d-4b02-aa22-76b841d64be7 · outbound

This paper cites Chal- lenges and opportunities in quantum machine learning.Nature computational science, 2(9):567– 576, 2022.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Chal- lenges and opportunities in quantum machine learning.Nature computational science, 2(9):567– 576, 2022

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5de2abf-b252-4464-808f-9fa876857661 · outbound

This paper cites Córcoles, Kristan Temme, Aram W.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Córcoles, Kristan Temme, Aram W

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfa71f6a-881c-4a3d-9a9b-4f8044b61f60 · outbound

This paper cites McMahon, Colin Scarato,FrancoisSwiadek,ChristianKraglundAndersen,ChristophHellings,SebastianKrinner, Nathan Lacroix, Stefania Lazar, Michael Kerschbaum, Dante Colao Zanuz, Graham J.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool McMahon, Colin Scarato,FrancoisSwiadek,ChristianKraglundAndersen,ChristophHellings,SebastianKrinner, Nathan Lacroix, Stefania Lazar, Michael Kerschbaum, Dante Colao Zanuz, Graham J

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1785933-cba5-4284-988b-ef4fc787f294 · outbound

This paper cites Munro, Yong Heng Huo, Chao Yang Lu, Cheng Zhi Peng, Xiaobo Zhu, and Jian Wei Pan.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Munro, Yong Heng Huo, Chao Yang Lu, Cheng Zhi Peng, Xiaobo Zhu, and Jian Wei Pan

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28939b50-ffe3-46e4-9508-a2a16c9fcc3b · outbound

This paper cites Anartificialneuron implemented on an actual quantum processor.npj Quantum Information, 5(1):26, 2019.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Anartificialneuron implemented on an actual quantum processor.npj Quantum Information, 5(1):26, 2019

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84d6c9ca-fdfb-4edf-8642-cb403664502f · outbound

This paper cites Experimental quantum generative adversarial networks for image generation.Physical Review Applied, 16(2):024051, 2021.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Experimental quantum generative adversarial networks for image generation.Physical Review Applied, 16(2):024051, 2021

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cc52e2e-6879-4123-b11e-e6b034a64873 · outbound

This paper cites Quantum generative adversarial networks with multiple superconducting qubits.npj Quantum Information, 7(1):165, 2021.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Quantum generative adversarial networks with multiple superconducting qubits.npj Quantum Information, 7(1):165, 2021

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd89d0f3-c5a2-4bf7-9578-94dce5342e75 · outbound

This paper cites Experimental demonstration of quantum continual learning with superconducting qubits.npj Quantum Information, 12(1):28, 2026.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Experimental demonstration of quantum continual learning with superconducting qubits.npj Quantum Information, 12(1):28, 2026

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40673b13-f638-4a0a-aafc-0fe8f0e53128 · outbound

This paper cites Quantumensemblelearningwithaprogrammablesuperconducting processor.npj Quantum Information, 11(1):83, 2025.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Quantumensemblelearningwithaprogrammablesuperconducting processor.npj Quantum Information, 11(1):83, 2025

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c688a20b-b8c6-4340-b783-d17a7f7867b3 · outbound

This paper cites TensorFlow Quantum: A Software Framework for Quantum Machine Learning.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool TensorFlow Quantum: A Software Framework for Quantum Machine Learning

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T07:13:16.782950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b8fd1184-f063-4972-b2c4-f68f394681c1 · outbound

This paper cites Quantumadversarialmachinelearning.Physical Review Research, 2(3):033212, 2020.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Quantumadversarialmachinelearning.Physical Review Research, 2(3):033212, 2020

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2af27fcb-abd6-4dfb-b8d0-7402434c08ff · outbound

This paper cites Vulnerability of quantum classification to adversarial perturbations.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Vulnerability of quantum classification to adversarial perturbations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22777a19-09fe-4141-860d-391b5f06d3c9 · outbound

This paper cites Predominantaspectsonsecurityforquantummachinelearning:Lit- eraturereview.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Predominantaspectsonsecurityforquantummachinelearning:Lit- eraturereview

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4fd260e-be03-4f3f-9715-9cbdc95d2dd3 · outbound

This paper cites Adversarialmachinelearning.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Adversarialmachinelearning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffe11ffe-1f2c-4d5f-9479-d8236a102f22 · outbound

This paper cites Explainingandharnessingadversarial examples.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Explainingandharnessingadversarial examples

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f6e6c3b-5781-4873-a3a1-be0baa95f374 · outbound

This paper cites Cam- bridge university press, 2010.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Cam- bridge university press, 2010

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2ba4b11-f90a-4fc6-b462-ea39fe6c0d97 · outbound

This paper cites Robustness verification of quantum classifiers.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Robustness verification of quantum classifiers

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f495d052-b6e4-4969-9354-95025da019a1 · outbound

This paper cites A robustness verification tool for quantum machine learning models.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool A robustness verification tool for quantum machine learning models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2b1be67-7dcf-4819-86cd-1e43ddd84108 · outbound

This paper cites Vasilakos, Yang Yang, Yu-Chun Wu, Ji Guan, Peng Duan, and Guo-Ping Guo.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Vasilakos, Yang Yang, Yu-Chun Wu, Ji Guan, Peng Duan, and Guo-Ping Guo

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04cab05b-df2a-48ac-a218-9c2686e6142d · outbound

This paper cites Reluplex: An efficient smt solver for verifying deep neural networks.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Reluplex: An efficient smt solver for verifying deep neural networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffae0769-2b3e-428c-865b-3eb7fe3efb30 · outbound

This paper cites An approach to reachability analysis for feed-forward ReLU neural networks.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool An approach to reachability analysis for feed-forward ReLU neural networks

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-06-29T07:13:16.773082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8b44ff99-9644-4956-80f5-f5da5b4d34ab · outbound

This paper cites Xiao, and Russ Tedrake.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Xiao, and Russ Tedrake

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e64bbff-e0f5-4cf7-95c9-55c4245517b2 · outbound

This paper cites Measuring neural net robustness with constraints.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Measuring neural net robustness with constraints

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24b224f3-051b-4e48-9368-5c375c20cc9b · outbound

This paper cites Verification of deep convolutional neural networks using imagestars.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Verification of deep convolutional neural networks using imagestars

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7294ec52-dc30-4216-9a31-8dacc1350f24 · outbound

This paper cites Adversarial attacks and defenses in deep learning.Engineering, 6(3):346–360, 2020.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Adversarial attacks and defenses in deep learning.Engineering, 6(3):346–360, 2020

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 621017e4-2311-4b83-bf3d-7713f33ef28d · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Explaining and Harnessing Adversarial Examples

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-06-29T07:13:16.787016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 668c1969-d7f9-4142-a6da-647b39b4029e · outbound

This paper cites General parameter-shift rules for quantum gradients.Quantum, 6:677, 2022.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool General parameter-shift rules for quantum gradients.Quantum, 6:677, 2022

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73ec5592-0936-46b7-b5f2-a92dae6111da · outbound

This paper cites Physical Review A, 98(3):032309, 2018.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Physical Review A, 98(3):032309, 2018

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92d1f3fc-e9c5-4fa2-bbd0-98a6cbbf3223 · outbound

This paper cites Evaluating analytic gradients on quantum hardware.Physical Review A, 99(3):032331, 2019.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Evaluating analytic gradients on quantum hardware.Physical Review A, 99(3):032331, 2019

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bae80276-8fae-43f8-9839-bdaf30cdac9f · outbound

This paper cites In2018 IEEE Conference on Decision and Control (CDC), pages 1624–1631.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool In2018 IEEE Conference on Decision and Control (CDC), pages 1624–1631

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2ef53f5-da41-4cda-be53-52b4611597c9 · outbound

This paper cites An abstraction-based framework for neural network verification.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool An abstraction-based framework for neural network verification

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d790527e-be5c-4e34-82ee-cb8e41c062b4 · outbound

This paper cites Formal analysis and redesign of a neural network-based aircraft taxiing system with verifai.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Formal analysis and redesign of a neural network-based aircraft taxiing system with verifai

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88a07aec-8577-4da1-9fd7-34d2f5f8f4d2 · outbound

This paper cites Safetyverificationfordeepneuralnetworkswithprovableguarantees(in- vitedpaper).

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Safetyverificationfordeepneuralnetworkswithprovableguarantees(in- vitedpaper)

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a3e334e-4d1d-4bd0-86a9-c46a360b8e51 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Towards deep learning models resistant to adversarial attacks

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c2a3862-dd21-450a-a485-d13aac8886c3 · outbound

This paper cites Prentice Hall Professional, 2006.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Prentice Hall Professional, 2006

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a84ccde-220d-42a4-bb43-3422041b5855 · outbound

This paper cites Open Quantum Assembly Language.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Open Quantum Assembly Language

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-06-29T07:13:16.777879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9a3f7b95-41e5-4a19-ae1c-557ee69b2441 · outbound

This paper cites Quantumnoiseprotects quantum classifiers against adversaries.Physical Review Research, 3(2):023153, 2021.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Quantumnoiseprotects quantum classifiers against adversaries.Physical Review Research, 3(2):023153, 2021

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1560714a-8823-4643-ae0b-e2b156496708 · outbound

This paper cites Verifying fairness in quantum machine learning.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Verifying fairness in quantum machine learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e697024c-27ba-4751-b331-87c35aa0cb97 · outbound

This paper cites Certifiedrobustnessofquantumclassifiersagainstadversarialexamplesthrough quantum noise.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Certifiedrobustnessofquantumclassifiersagainstadversarialexamplesthrough quantum noise

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f528cf5e-74b7-46aa-9d30-aa1a99419a16 · outbound

This paper cites Emnist:Extendingmnist to handwritten letters.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Emnist:Extendingmnist to handwritten letters

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a907ce1-d318-4692-9fb2-439a2cc5c5d9 · outbound

This paper cites Adversarial robustness of deep neural networks: A survey from a formal verification perspective.IEEE Transactions on Dependable and Secure Computing, 2022.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Adversarial robustness of deep neural networks: A survey from a formal verification perspective.IEEE Transactions on Dependable and Secure Computing, 2022

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67dc36ec-25b0-4db2-862a-19afa049d934 · outbound

This paper cites Detecting violations of differen- tial privacy for quantum algorithms.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Detecting violations of differen- tial privacy for quantum algorithms

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b870af6-303c-40b4-a80d-884b56b748f5 · outbound

This paper cites Optimal mechanisms for quantum local differential privacy.

Verifying Adversarial Robustness in Quantum Machine Learning: from theory to physical validation via a software tool Optimal mechanisms for quantum local differential privacy

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-29T07:06:14.748337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.