Paper Citation Record · LEDGER

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges

As of 7 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 2 inbound Pith citation observations for arXiv:2506.20008.

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

pith.paper-citation-record.v1
2506.20008 v2

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:04:27.281856Z

measured 29 of 29 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T16:36:03.557894Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T17:13:45.118829Z

Reference resolution

27 of 27 outbound references displayed

verified exact1
verified fuzzy17
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 940f05fe-0f30-455e-888b-459e934fa41b · outbound

This paper cites Quantum supremacy using a programmable superconducting processor,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Quantum supremacy using a programmable superconducting processor,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.890739Z

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 d076161d-3052-490d-82ef-db38bfb484cd · outbound

This paper cites Computational advantage in hybrid quantum neural networks: Myth or reality?.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Computational advantage in hybrid quantum neural networks: Myth or reality?

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.880714Z

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 176e4bc9-35ce-4dea-8c80-9a49a5e829b7 · outbound

This paper cites Demonstrating quantum advantage in hybrid quantum neural networks for model capacity,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Demonstrating quantum advantage in hybrid quantum neural networks for model capacity,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.870732Z

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 e87dadbc-8641-4dcc-884d-703381e821a1 · outbound

This paper cites PennyLane: Automatic differentiation of hybrid quantum-classical computations.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges PennyLane: Automatic differentiation of hybrid quantum-classical computations

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:04:27.096707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93a7f962-10fa-4f45-95df-063e57e7f0ba · outbound

This paper cites Quantum machine learning,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Quantum machine learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.860996Z

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 · outbound

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

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 cfb5ef01-6ec3-494a-ba1c-555253e86b21 · outbound

This paper cites Optimizing low-energy carbon IIOT systems with quantum algorithms: Performance evaluation and noise robustness,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Optimizing low-energy carbon IIOT systems with quantum algorithms: Performance evaluation and noise robustness,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.834003Z

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 33065f6b-8154-47a1-819e-b2ca1715b363 · outbound

This paper cites Qnn-vrcs: A quantum neural network for vehicle road cooperation systems,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Qnn-vrcs: A quantum neural network for vehicle road cooperation systems,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.792679Z

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 8e804a83-a305-46c9-8b62-7d3fc3d65aba · outbound

This paper cites Next-generation quantum neural networks: Enhancing efficiency, security, and privacy,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Next-generation quantum neural networks: Enhancing efficiency, security, and privacy,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.761967Z

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 26cae801-4eb8-469f-81db-2fd4989af578 · outbound

This paper cites Survey of different large language model architectures: Trends, benchmarks, and challenges,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Survey of different large language model architectures: Trends, benchmarks, and challenges,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.750916Z

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 f2b353c1-36b7-4395-9f06-966c077a8b8b · outbound

This paper cites Qiskit Code Assistant: Training LLMs for generating Quantum Computing Code.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Qiskit Code Assistant: Training LLMs for generating Quantum Computing Code

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:04:27.168250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9f2bfe1-7431-4ca9-86cf-041e8ddc34b1 · outbound

This paper cites Qiskit HumanEval: An Evaluation Benchmark For Quantum Code Generative Models.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Qiskit HumanEval: An Evaluation Benchmark For Quantum Code Generative Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:04:27.171751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f32e18d-209e-4020-b866-c1fb4d41406f · outbound

This paper cites Evaluating Large Language Models Trained on Code.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Evaluating Large Language Models Trained on Code

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:04:27.185441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27c3a9b7-1d6f-4c89-a061-18b4df93dbdd · outbound

This paper cites StarCoder: may the source be with you!.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges StarCoder: may the source be with you!

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:04:27.195381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1334b2f0-22ce-4342-8603-6cd4c94b9918 · outbound

This paper cites Program Synthesis with Large Language Models.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Program Synthesis with Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:04:27.205160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82b5231d-3719-42b5-8711-be83fbd79d90 · outbound

This paper cites QHack 2022 - the one-of-a-kind celebration of quantum computing,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges QHack 2022 - the one-of-a-kind celebration of quantum computing,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.738455Z

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 d13d142b-ec2d-481d-bb01-3050aa4510f2 · outbound

This paper cites Introducing qiskit code assistant,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Introducing qiskit code assistant,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.727376Z

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 c5b57925-a6f8-4e27-ab62-d19ea27608c9 · outbound

This paper cites Pennycoder: Efficient domain-specific llms for pennylane- based quantum code generation,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Pennycoder: Efficient domain-specific llms for pennylane- based quantum code generation,

Reference 18

Resolution: verified exact; raw_fallback, observed 2026-08-06T23:04:27.434320Z

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 2304b6da-98a0-4646-b4ab-0c5efae7f847 · outbound

This paper cites Cirq: A python framework for creating, editing, and invoking noisy intermediate scale quantum (nisq) circuits,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Cirq: A python framework for creating, editing, and invoking noisy intermediate scale quantum (nisq) circuits,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.712072Z

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 5e4efb18-2477-404f-9f51-364c199f78ce · outbound

This paper cites Accelerate quantum software development on amazon braket with claude-3,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Accelerate quantum software development on amazon braket with claude-3,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.697433Z

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 a91e04f3-68fc-42ae-927f-55e17de5882e · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T23:04:27.234748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce67028c-6c94-492d-9dea-2cd94dbb8981 · outbound

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

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges A PennyLane-Centric Dataset to Enhance LLM-based Quantum Code Generation using RAG

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T23:04:27.237817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbf8bee7-cbba-4c32-aa47-491dc3d38417 · outbound

This paper cites Wooldridge, An Introduction to MultiAgent Systems.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Wooldridge, An Introduction to MultiAgent Systems

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.677943Z

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 13285b05-806a-4734-8a47-20d368bfea63 · outbound

This paper cites Rgd: Multi-llm based agent debugger via refinement and generation guidance,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Rgd: Multi-llm based agent debugger via refinement and generation guidance,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.666930Z

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 6496d2ca-8193-43c4-93bf-5a7093341c98 · outbound

This paper cites Coast: Enhancing the code debugging ability of llms through communicative agent based data synthesis,.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Coast: Enhancing the code debugging ability of llms through communicative agent based data synthesis,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.648764Z

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 2d3799ec-9fcb-4922-94ad-3d3fb079e9c2 · outbound

This paper cites Qhack 2023 coding challenges.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Qhack 2023 coding challenges

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.636210Z

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 4621d267-4c06-4d9f-b920-a782497f920c · outbound

This paper cites Qhack 2024 coding challenges.

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges Qhack 2024 coding challenges

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:04:27.621344Z

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.

Pith citing papers

Observation b8771b51-cc23-4c47-9444-db8833c5a160 · inbound

StabilizerBench: A Benchmark for AI-Assisted Quantum Error Correction Circuit Synthesis cites this paper.

StabilizerBench: A Benchmark for AI-Assisted Quantum Error Correction Circuit Synthesis QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-09T22:34:07.367367Z

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 19dc2533-7d04-402c-83c1-5091a98e58c9 · inbound

Qiskit QuantumKatas: Adapting Microsoft's Quantum Computing exercises for LLM evaluation cites this paper.

Qiskit QuantumKatas: Adapting Microsoft's Quantum Computing exercises for LLM evaluation QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-29T17:13:45.120983Z

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.