Paper Citation Record · LEDGER

Optimizing Ansatz Design in Quantum Generative Adversarial Networks Using Large Language Models

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2503.12884.

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

pith.paper-citation-record.v1
2503.12884 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:27:20.057704Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:09:41.964053Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8956002b-b3f2-4f84-8833-3195b0f40e90 · inbound

A Survey of Quantum Generative Adversarial Networks: Architectures, Use Cases, and Real-World Implementations cites this paper.

A Survey of Quantum Generative Adversarial Networks: Architectures, Use Cases, and Real-World Implementations Optimizing Ansatz Design in Quantum Generative Adversarial Networks Using Large Language Models

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.057704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fd489dc-2c7c-4957-9058-66f787815d3b · inbound

Generative quantum eigensolver with constrained circuit-cutting overhead cites this paper.

Generative quantum eigensolver with constrained circuit-cutting overhead Optimizing Ansatz Design in Quantum Generative Adversarial Networks Using Large Language Models

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:31:44.090986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c0975778-15c1-4fcc-a492-02234221ba8d · inbound

LLM-Guided Ans\"atze Design for Quantum Circuit Born Machines in Financial Generative Modeling cites this paper.

LLM-Guided Ans\"atze Design for Quantum Circuit Born Machines in Financial Generative Modeling Optimizing Ansatz Design in Quantum Generative Adversarial Networks Using Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T20:43:40.035638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63ae0563-fa86-4307-8617-eaf7f822d1b9 · inbound

Quantum Circuit Generation via test-time learning with large language models cites this paper.

Quantum Circuit Generation via test-time learning with large language models Optimizing Ansatz Design in Quantum Generative Adversarial Networks Using Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T05:02:35.573238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb7c45ee-d1e3-43f9-ac75-218f1cea2b8f · inbound

Fine-Tuning Large Language Models for Quantum Reasoning cites this paper.

Fine-Tuning Large Language Models for Quantum Reasoning Optimizing Ansatz Design in Quantum Generative Adversarial Networks Using Large Language Models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:09:41.965742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ee948edc-8118-4f71-8c82-35dbce98d1f2 · 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 Optimizing Ansatz Design in Quantum Generative Adversarial Networks Using Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T03:58:57.446427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.