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Paper Citation Record · LEDGER

A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2310.10315.

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

pith.paper-citation-record.v1
2310.10315 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:59:01.294551Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

14
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation bbc6a578-3aca-49e7-b89f-68fecad95ac5 · inbound

Use of Faulty States in Cat-Code Error Correction cites this paper.

Use of Faulty States in Cat-Code Error Correction A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 5

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verified exact
arxiv_id, observed 2026-05-23T07:15:28.667145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T07:13:24.521355Z digest=sha256:3e4c9ace0bdb33214da773ccd3245e1f7d5778c040b3cfe603b012a5acaf8cc7

Observation aa4e0d53-fc5b-45c6-bb89-c8bc9b0177a6 · inbound

A PennyLane-Centric Dataset to Enhance LLM-based Quantum Code Generation using RAG cites this paper.

A PennyLane-Centric Dataset to Enhance LLM-based Quantum Code Generation using RAG A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 6

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arxiv_id, observed 2026-05-23T01:42:23.244736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T01:41:25.033971Z digest=sha256:ee66684f0b12c810b886164c724a6b658e9e1dc31cf9b4664b8dc43bac4bb0fa

Observation 6634f8b7-af72-4331-8eb6-b45b0b15f934 · inbound

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges cites this paper.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 6

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no resolver link, observed 2026-08-06T23:04:27.118694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:04:27.118694Z digest=sha256:b9d11e69722e0c3073e114ad93303f5a4f5986d1e49cce0a8a095dded1581570

Observation 2d5695e5-d9ce-430b-b3fe-e75017e4c570 · inbound

Universal Fluctuations in the Tail Probability for d=2 Random Walks in Space-Time Random Environments cites this paper.

Universal Fluctuations in the Tail Probability for d=2 Random Walks in Space-Time Random Environments A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 37

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unresolved
no resolver link, observed 2026-08-05T17:37:37.276873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:37:37.276873Z digest=sha256:b19c421123e299c3f38786eb93d6e0a9f0f3460abc56ff28b998e7ca9baca602

Observation 474e5f28-d044-4cf4-98dd-32f8f234feb4 · inbound

RobQFL: Robust Quantum Federated Learning in Adversarial Environment cites this paper.

RobQFL: Robust Quantum Federated Learning in Adversarial Environment A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 36

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unresolved
no resolver link, observed 2026-08-05T05:51:20.752216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:51:20.752216Z digest=sha256:b96d264818b4da054b1f88a403b1c2605bb746f2421eecb59c9f81b50de88c60

Observation 60f291fe-33fa-4e9d-953c-878c35e41a42 · inbound

QNAS: A Neural Architecture Search Framework for Accurate and Efficient Quantum Neural Networks cites this paper.

QNAS: A Neural Architecture Search Framework for Accurate and Efficient Quantum Neural Networks A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 6

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verified exact
arxiv_id, observed 2026-05-11T00:25:53.182757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T18:31:10.419182Z digest=sha256:97ffb5d70070f82a5da0d1aba179a127771fa915b9d9a7f9f5941a732273bf5b

Observation 995b955a-9089-421d-9aa6-326c6c449790 · inbound

Domain-Aware Hybrid Quantum Learning via Correlation-Guided Circuit Design for Crime Pattern Analytics cites this paper.

Domain-Aware Hybrid Quantum Learning via Correlation-Guided Circuit Design for Crime Pattern Analytics A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 1

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arxiv_id, observed 2026-05-11T00:25:53.166669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T18:31:11.615697Z digest=sha256:f003d23c3e0574500578bfb7f1f8f6ec7ce6d4716286a667159aef7985baf7a4

Observation 4a224d3f-325b-4c4c-aba2-d3894f46f2b5 · inbound

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits cites this paper.

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 56

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arxiv_id, observed 2026-05-11T08:40:57.742044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:35:01.080061Z digest=sha256:645f2accc8f1ad98770117013053514064d6a119d6fd3e21e1da64d2985d5cce

Observation 3c2a00f2-ef1c-4394-99d4-f2846e982f89 · inbound

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits cites this paper.

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 56

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no resolver link, observed 2026-08-04T05:31:09.986717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:31:09.986717Z digest=sha256:d2f76f6b711ac488c83abb618bc24f2a818bfb5961dec16d7998c6f9f1410e4f

Observation ed8db7ed-66eb-491a-b2db-5cbc38ba09ee · inbound

Design Space Exploration of Hybrid Quantum Neural Networks for Chronic Kidney Disease cites this paper.

Design Space Exploration of Hybrid Quantum Neural Networks for Chronic Kidney Disease A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 3

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verified exact
arxiv_id, observed 2026-05-10T13:55:28.832660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T13:53:48.911054Z digest=sha256:8e473a69fe34b8c309a20a356127f7d7d8e7a3befcad840518ea787ded30ea41

Observation ea1e6189-dcd4-4479-b4a8-35786eb38f05 · inbound

GAT-QNN: Genetic Algorithm-Based Training of Hybrid Quantum Neural Networks cites this paper.

GAT-QNN: Genetic Algorithm-Based Training of Hybrid Quantum Neural Networks A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 5

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verified exact
arxiv_id, observed 2026-05-10T11:35:18.684778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T11:34:24.127678Z digest=sha256:756d24498a4f48b8a3a19df0976a9a2e5276ed0c0e3911b17cdf855160b29d34

Observation cbd1b1d3-4d98-43ac-80e9-c18b43a898e2 · inbound

Robustness Evaluation of Hybrid Quantum Neural Networks under Noise Models via System-Level Error Mitigation cites this paper.

Robustness Evaluation of Hybrid Quantum Neural Networks under Noise Models via System-Level Error Mitigation A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:36:01.765398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T05:33:25.684038Z digest=sha256:a8a4f77fc44f37108650b281e61f933e5dc6b6cffff287da423471d7d09d0b61

Observation 727fad24-45b0-4a4e-8e8c-0515a9ea4409 · inbound

Robustness Evaluation of Hybrid Quantum Neural Networks under Noise Models via System-Level Error Mitigation cites this paper.

Robustness Evaluation of Hybrid Quantum Neural Networks under Noise Models via System-Level Error Mitigation A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-02T15:57:26.411720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T15:57:26.411720Z digest=sha256:d6623584afe237ca8218d9ed0253b51b752f2c045dc4dcaadbb1c4f4f618c624

Observation 73d1d55a-9af5-4649-aa66-ababd2afb54f · inbound

Hybrid Quantum-Classical Neural Architecture Search cites this paper.

Hybrid Quantum-Classical Neural Architecture Search A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 2

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verified exact
arxiv_id, observed 2026-05-20T11:38:14.520820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T11:36:33.634850Z digest=sha256:69bd0cb700072d8f9f3704d716028c3c05460488afb4c3650d0e7a5c1e194175

Observation cc690796-be71-44a5-8f8c-38ac83bd89a5 · inbound

Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices cites this paper.

Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 3

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verified exact
arxiv_id, observed 2026-05-22T06:01:09.112404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T05:56:35.027295Z digest=sha256:a19ba35505239659ff0fd5b118b197bc55649e54e95b525106eded27d4caf27b

Observation 48621529-b900-4655-ab66-69131a141235 · inbound

Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices cites this paper.

Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 3

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unresolved
no resolver link, observed 2026-08-02T13:31:24.182447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:31:24.182447Z digest=sha256:2ed1d3fa472ae3e8b18b80fa3e01e2c765f44c14783ffb50f67e1e6a121e4a68

Observation c2602c56-2132-4a9c-b31f-ec96729dea02 · inbound

PennySynth: RAG-Driven Data Synthesis for Automated Quantum Code Generation cites this paper.

PennySynth: RAG-Driven Data Synthesis for Automated Quantum Code Generation A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 3

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verified exact
arxiv_id, observed 2026-06-29T21:43:59.574958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T21:37:50.495550Z digest=sha256:40f85fed2dfb9eefd4ca66f552e8b8b3296878630b2d0e6168a4a14375727980

Observation 819ed617-aaf3-48d1-bd55-4bc8db08aa8e · inbound

PennySynth: RAG-Driven Data Synthesis for Automated Quantum Code Generation cites this paper.

PennySynth: RAG-Driven Data Synthesis for Automated Quantum Code Generation A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 3

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unresolved
no resolver link, observed 2026-08-02T13:13:44.293451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:13:44.293451Z digest=sha256:3321307f230cb63e12722c381ec6a876a247345acf8f7087970f777fc69f3404

Observation b63b74d6-7e33-4cd2-8d4b-849265a70f4f · inbound

Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework cites this paper.

Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 147

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verified exact
arxiv_id, observed 2026-06-28T16:52:23.806644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T16:50:33.599459Z digest=sha256:84dbe5dd45dedae0fdf492773f95d2672ce48d266ce4878ae4a2500338171ea7

Observation 81aed66f-0134-4ac3-9820-7bbd78960dfa · inbound

Private training in quantum machine learning cites this paper.

Private training in quantum machine learning A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 8

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verified exact
arxiv_id, observed 2026-06-30T08:04:28.924941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T07:36:50.442735Z digest=sha256:4cb9ffeb44504c66baf76bf93f97fee822460c704798b6d9b64f30879b265379

Observation 50b8d685-60b7-4f91-b067-03075ee0394d · inbound

Private training in quantum machine learning cites this paper.

Private training in quantum machine learning A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 8

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unresolved
no resolver link, observed 2026-07-12T11:02:29.066725Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T11:02:29.066725Z digest=sha256:14a0286c2b10e112708d4fb516a5375adfc748ea3892ce9c8f64a8342c061726

Observation f7af91e1-a9d1-4b60-b484-86b218eced8d · inbound

An efficient Pauli decomposition algorithm for structured matrices cites this paper.

An efficient Pauli decomposition algorithm for structured matrices A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 13

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verified exact
arxiv_id, observed 2026-07-01T05:05:23.605083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-01T05:00:09.939428Z digest=sha256:6b73488aec6f57c8b1d786fe694c367389373e1db4c8efb1b1dcc97b5ecec010

Observation 67ad22a7-6315-4ffa-ab29-a0251e1f7c6f · inbound

VQCSim: When Does Compile-Once Statevector Simulation Beat Generic Quantum Frameworks? cites this paper.

VQCSim: When Does Compile-Once Statevector Simulation Beat Generic Quantum Frameworks? A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 28

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unresolved
no resolver link, observed 2026-08-02T06:55:10.438204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:55:10.438204Z digest=sha256:9bb9e0a1d1d3b2f0e30651651e3961ed8a012bc197e934c1412b838e93c557b6

Observation 8122b7eb-3a82-4988-b737-65acc73154b4 · inbound

Towards quantum machine learning for assessing the resilience of post-quantum cryptography cites this paper.

Towards quantum machine learning for assessing the resilience of post-quantum cryptography A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 40

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no resolver link, observed 2026-08-02T03:58:57.535965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T03:58:57.535965Z digest=sha256:3be55b3df8526248f9230e023b5dc5072a9dab8cf40b7a0cb2b28b1e64e1cd83

Observation 7c5ad4ce-8726-440e-8d2e-a6b5e277e814 · inbound

Volcanic Clouds Detection through QCNN and Geostationary Satellite Multispectral Imagery cites this paper.

Volcanic Clouds Detection through QCNN and Geostationary Satellite Multispectral Imagery A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 7

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unresolved
no resolver link, observed 2026-08-04T01:30:19.336814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T01:30:19.336814Z digest=sha256:590d750c09919d855e1d572821794d6bf9a134494aea71e16a337b20963bf6af

Observation 2fd14344-4b30-4a18-b66e-6de0e55c009a · inbound

Learning to Rank Tensor Network Contraction Plans for GPU-Accelerated Quantum Circuit Simulation cites this paper.

Learning to Rank Tensor Network Contraction Plans for GPU-Accelerated Quantum Circuit Simulation A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead

Reference 14

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unresolved
no resolver link, observed 2026-08-07T22:59:01.294551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:59:01.294551Z digest=sha256:dd2c2677c3c20a36976423786e06c4bd37f122f178ad7a41a0a16861955611a5