Paper Citation Record · LEDGER

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

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 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 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:04:27.118694Z

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

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: verified exact; 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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: verified exact; 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: verified exact; 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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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.

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.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.