Paper Citation Record · LEDGER

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

As of 19 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 6 inbound Pith citation observations for arXiv:2504.16350.

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

pith.paper-citation-record.v1
2504.16350 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:13:03.933928Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T23:29:01.446024Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T09:16:49.184051Z

Reference resolution

35 of 35 outbound references displayed

verified exact0
verified fuzzy22
unresolved13
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0b261d2a-32f5-40a3-aae2-e94701552d34 · outbound

This paper cites Quantum computing for finance.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Quantum computing for finance

Reference 1

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Observation 16b6117b-2079-4f68-b916-ad8a85367c38 · outbound

This paper cites Quantum chemistry in the age of quantum computing.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Quantum chemistry in the age of quantum computing

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.414131Z

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Observation 045562a7-943c-4791-a9d7-89b318039918 · outbound

This paper cites Quantum-centric supercomputing for materials science: A perspective on challenges and future directions.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Quantum-centric supercomputing for materials science: A perspective on challenges and future directions

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.402090Z

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Observation 0603792e-6f03-4256-bdcf-1b0588cd4c50 · outbound

This paper cites an unresolved cited work.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Unresolved cited work

Reference 4

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Observation d5332dda-9905-49fb-94b9-7a00831787de · outbound

This paper cites Quantum machine learning.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Quantum machine learning

Reference 5

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Source-reported events for the cited work

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Observation 18c144b9-963a-4be4-9fd1-2edc260fc733 · outbound

This paper cites A Quantum Approximate Optimization Algorithm.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits A Quantum Approximate Optimization Algorithm

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T11:13:03.819149Z

Source-reported events for the cited work

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Observation db58f651-0d36-43e1-b716-6588888d9c04 · outbound

This paper cites A review on quantum approximate optimization algorithm and its variants.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits A review on quantum approximate optimization algorithm and its variants

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.370351Z

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Observation 1e92e87e-8da4-4bba-8880-41c1dace54bf · outbound

This paper cites Adaptive quantum approximate optimization algorithm for solving combinato- rial problems on a quantum computer.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Adaptive quantum approximate optimization algorithm for solving combinato- rial problems on a quantum computer

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.358588Z

Source-reported events for the cited work

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Observation bed5a84f-7a46-4774-afc6-fcfd44525e01 · outbound

This paper cites An adaptive variational algorithm for exact molecular simula- tions on a quantum computer.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits An adaptive variational algorithm for exact molecular simula- tions on a quantum computer

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.347219Z

Source-reported events for the cited work

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Observation c3d6b4d7-120d-491f-bd0f-5ece5fab8d6d · outbound

This paper cites Layer VQE: A variational approach for combinatorial optimization on noisy quantum computers.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Layer VQE: A variational approach for combinatorial optimization on noisy quantum computers

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.334983Z

Source-reported events for the cited work

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Observation ccffcd30-9e0c-49f1-9d9d-57095e03d320 · outbound

This paper cites GroverGPT: A Large Language Model with 8 Billion Parameters for Quantum Searching.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits GroverGPT: A Large Language Model with 8 Billion Parameters for Quantum Searching

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T11:13:03.838062Z

Source-reported events for the cited work

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Observation 063f243c-2a8d-4c55-983d-44d1a8dbd756 · outbound

This paper cites The generative quantum eigensolver (gqe) and its application for ground state search.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits The generative quantum eigensolver (gqe) and its application for ground state search

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T11:13:03.842224Z

Source-reported events for the cited work

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Observation 42d239de-ca9e-4287-bee9-612f5e61e9d1 · outbound

This paper cites cuquantum sdk: A high-performance library for accelerating quantum science.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits cuquantum sdk: A high-performance library for accelerating quantum science

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.321854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f57efdb1-de23-4e3b-9b12-f60ed5f2b12d · outbound

This paper cites NVIDIA CUDA-Q framework.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits NVIDIA CUDA-Q framework

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.308973Z

Source-reported events for the cited work

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Observation a47e6e9f-243a-4243-b488-04cf7a4b19e6 · outbound

This paper cites Some simplified np-complete problems.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Some simplified np-complete problems

Reference 15

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Source-reported events for the cited work

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Observation 63131c22-0f59-4e8f-869c-1c3548665a57 · outbound

This paper cites Quantum bridge analytics i: a tutorial on formulating and using qubo models.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Quantum bridge analytics i: a tutorial on formulating and using qubo models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.289287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation af09478f-b374-42c2-8e70-11578e987f67 · outbound

This paper cites A Tutorial on Formulating and Using QUBO Models.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits A Tutorial on Formulating and Using QUBO Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T11:13:03.860889Z

Source-reported events for the cited work

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Observation a35620c0-0dfd-472c-a51f-a54da417e0a6 · outbound

This paper cites Multilevel combi- natorial optimization across quantum architectures.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Multilevel combi- natorial optimization across quantum architectures

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.277479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation da862a08-f4bf-4f2e-8e4c-c3f87d3341b8 · outbound

This paper cites Hybrid quantum-classical algorithms for approximate graph coloring.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Hybrid quantum-classical algorithms for approximate graph coloring

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.266143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9412cbf4-298e-47d6-87a0-b7fb7799c51b · outbound

This paper cites Equivariant QAOA and the Duel of the Mixers.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Equivariant QAOA and the Duel of the Mixers

Reference 20

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Source-reported events for the cited work

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Observation 776e92be-dad6-4426-b5af-89d1b515b12a · outbound

This paper cites Improving language understanding by generative pre-training.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Improving language understanding by generative pre-training

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T11:13:03.877100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 067c5310-580c-4f3c-9e85-8816ddf52f11 · outbound

This paper cites Attention is all you need.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Attention is all you need

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T11:13:03.881557Z

Source-reported events for the cited work

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Observation c893c673-a4f3-4e32-8c41-01cfded45b4f · outbound

This paper cites Evaluating Large Language Models Trained on Code.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Evaluating Large Language Models Trained on Code

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T11:13:03.886248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4a9c37c-43b1-47fa-8b72-fd5609f6e41a · outbound

This paper cites Characteristic functions on graphs: Birds of a feather, from statistical descriptors to parametric models.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Characteristic functions on graphs: Birds of a feather, from statistical descriptors to parametric models

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.240278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b4cc8d2a-9d69-4964-a6ca-7ca8b32806ca · outbound

This paper cites Rank-two relaxation heuristics for max-cut and other binary quadratic programs.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Rank-two relaxation heuristics for max-cut and other binary quadratic programs

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.226078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8aaba245-d467-4f5b-b536-fd26c388add5 · outbound

This paper cites Classi- cal symmetries and the quantum approximate optimization algorithm.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Classi- cal symmetries and the quantum approximate optimization algorithm

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.214622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 39243a9f-ca49-4b0b-bf92-d8f61ce3095e · outbound

This paper cites Graph repre- sentation learning for parameter transferability in quantum approximate optimization algorithm.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Graph repre- sentation learning for parameter transferability in quantum approximate optimization algorithm

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.203254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 78a62a3b-6183-4586-9f15-54af177af1fb · outbound

This paper cites Similarity-based parameter transferability in the quantum approximate optimization algorithm.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Similarity-based parameter transferability in the quantum approximate optimization algorithm

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.191097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cf877408-22c5-4db0-b59e-a9da5f288e66 · outbound

This paper cites Hagberg, D.A.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Hagberg, D.A

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.177015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 26968ac8-a709-4f91-8ec1-a6fa1c5fc849 · outbound

This paper cites Generative quantum combinatorial optimization by means of a novel conditional generative quantum eigensolver.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Generative quantum combinatorial optimization by means of a novel conditional generative quantum eigensolver

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T11:13:03.913692Z

Source-reported events for the cited work

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Observation 3a1c896e-9797-46b9-a41c-943f98fde34b · outbound

This paper cites NVIDIA CUDA-Q.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits NVIDIA CUDA-Q

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.163183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation caba5070-0e04-413c-957b-0bad5e7befe9 · outbound

This paper cites NVIDIA DGX Quantum.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits NVIDIA DGX Quantum

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.150709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 75c9839f-d2b7-42ab-8467-6f0eb49e973f · outbound

This paper cites Mlqaoa: Graph learning ac- celerated hybrid quantum-classical multilevel qaoa.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Mlqaoa: Graph learning ac- celerated hybrid quantum-classical multilevel qaoa

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.138154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ae2ffcfe-9006-4c60-87e9-ce6ea20aa0e0 · outbound

This paper cites Scal- ing up the quantum divide and conquer algorithm for combinatorial optimization.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Scal- ing up the quantum divide and conquer algorithm for combinatorial optimization

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:13:04.125847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e3286b1a-13d4-4059-9af4-c0bc0cb034b5 · outbound

This paper cites Scaling Up the Quantum Divide and Conquer Algorithm for Combinatorial Optimization.

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits Scaling Up the Quantum Divide and Conquer Algorithm for Combinatorial Optimization

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-16T11:13:03.933928Z

Source-reported events for the cited work

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Pith citing papers

Observation 9b61955e-09c4-450d-b491-a40dedb860bd · inbound

Direct entanglement ansatz learning (DEAL) with ZNE on error-prone superconducting qubits cites this paper.

Direct entanglement ansatz learning (DEAL) with ZNE on error-prone superconducting qubits QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:45:12.388926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5fa5fc71-8757-41fc-b05e-0c9e813ede01 · inbound

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

Generative quantum eigensolver with constrained circuit-cutting overhead QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:31:44.081603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4d958d2a-3249-4420-865c-e42a1f60c4a0 · inbound

Scaling Quantum Optimization for Unit Commitment via Pauli Correlation Encoding cites this paper.

Scaling Quantum Optimization for Unit Commitment via Pauli Correlation Encoding QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:43:22.605273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f9cd5387-de1b-4347-86cf-3c4e120f891a · inbound

Setting angles in quantum approximate optimization at utility-scale cites this paper.

Setting angles in quantum approximate optimization at utility-scale QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-07-02T09:16:49.185573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3b5f64cd-1e67-4d22-8686-0f01e4ffdaff · inbound

Performance Model for Hybrid Quantum-Classical Workflows cites this paper.

Performance Model for Hybrid Quantum-Classical Workflows QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-01T23:29:01.446024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2107182b-e145-4a7d-9138-3cb86cf6434f · inbound

Learning to Prepare Molecular Ground States with Transformer Models cites this paper.

Learning to Prepare Molecular Ground States with Transformer Models QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T04:45:21.563369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.