Paper Citation Record · LEDGER

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing

As of 8 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2505.16332.

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

pith.paper-citation-record.v1
2505.16332 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:07:24.369032Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy24
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c5cf3473-ff90-459a-922c-b7772c25a2e4 · outbound

This paper cites Physics-inspired optimization for quadratic unconstrained problems using adigital annealer.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Physics-inspired optimization for quadratic unconstrained problems using adigital annealer

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:28.389344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 53ee2819-97e5-451f-8788-610a70681498 · outbound

This paper cites On the computational complexity of ising spin glass models.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing On the computational complexity of ising spin glass models

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:28.275438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 427ec362-27e2-4cc9-9db5-2fd25f17c7d9 · outbound

This paper cites an unresolved cited work.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:07:28.107839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 666a8276-3fd9-418f-b676-1bf647fc79a1 · outbound

This paper cites Quan- tum permutation synchronization, in: Proceedings of the IEEE/CVF ConferenceonComputerVisionandPatternRecognition,pp.13122– 13133.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Quan- tum permutation synchronization, in: Proceedings of the IEEE/CVF ConferenceonComputerVisionandPatternRecognition,pp.13122– 13133

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:27.869776Z

Source-reported events for the cited work

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Observation e80f9056-df1c-4ae3-b91e-69bc2cf3d4d9 · outbound

This paper cites Dynamical channel pruning by conditional accuracy change for deep neural networks.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Dynamical channel pruning by conditional accuracy change for deep neural networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:27.694238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d2720367-c24d-4492-afdf-4f48899f8e0f · outbound

This paper cites Quboformulationsfor training machine learning models.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Quboformulationsfor training machine learning models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:27.470958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 96c378ab-2551-4677-8817-b454a008e5d2 · outbound

This paper cites Learned Step Size Quantization.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Learned Step Size Quantization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:22.600554Z

Source-reported events for the cited work

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Observation 92c282f9-0bb6-4666-8603-91a7324209b4 · outbound

This paper cites Knowledgedistillation: Asurvey.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Knowledgedistillation: Asurvey

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:27.191183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fbf3234b-6cd5-4818-bc9f-78605cca2f3b · outbound

This paper cites Benchmarking quantum annealing controls with portfolio optimization.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Benchmarking quantum annealing controls with portfolio optimization

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:27.020139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e2051e34-baa8-4849-9e62-ea40d49e0bb0 · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:22.773473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfd9af47-c14f-448b-8f58-a3bcef73d531 · outbound

This paper cites Opq: Com- pressing deep neural networks with one-shot pruning-quantization, in:ProceedingsoftheAAAIconferenceonartificialintelligence,pp.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Opq: Com- pressing deep neural networks with one-shot pruning-quantization, in:ProceedingsoftheAAAIconferenceonartificialintelligence,pp

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:26.801092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 84f0c924-ee38-41e1-a5a4-c85327587a52 · outbound

This paper cites Benchmarking quantum (-inspired) annealing hardware on practical use cases.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Benchmarking quantum (-inspired) annealing hardware on practical use cases

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:26.562219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6c9ce822-f3d4-49e0-868a-fbdeb9335638 · outbound

This paper cites The advantage quantum computer.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing The advantage quantum computer

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:26.350371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 695a7d91-7ee9-43a7-8483-c27421ca9d5b · outbound

This paper cites Traffic signal optimization on a square lattice using the d-wave quan- tum annealer.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Traffic signal optimization on a square lattice using the d-wave quan- tum annealer

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:26.224954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c1e56bc3-27be-4364-b446-fb1d3ddcf1e1 · outbound

This paper cites Pruning and quantization for deep neural network acceleration: A survey.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Pruning and quantization for deep neural network acceleration: A survey

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:26.083567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 63cf5697-8e55-468a-b27e-78da914275be · outbound

This paper cites Maximum cuts and large bipartite sub- graphs.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Maximum cuts and large bipartite sub- graphs

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:25.939882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8fb9922a-edcd-4c87-ab41-d16483b93ff2 · outbound

This paper cites Pruning tutorial.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Pruning tutorial

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:25.724948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e82c7849-aa0c-4ff4-8e4a-7b1d2c5f1c8b · outbound

This paper cites Quantization.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Quantization

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:25.523765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f9e0f6cf-e6f0-45ba-9069-6c38f0c6baf9 · outbound

This paper cites Applica- tion of digital annealer for faster combinatorial optimization.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Applica- tion of digital annealer for faster combinatorial optimization

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:25.416491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 508afb0e-26b5-48f6-a357-13a2e895e161 · outbound

This paper cites The german trafficsignrecognitionbenchmark:amulti-classclassificationcompe- tition,in:The2011internationaljointconferenceonneuralnetworks, IEEE.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing The german trafficsignrecognitionbenchmark:amulti-classclassificationcompe- tition,in:The2011internationaljointconferenceonneuralnetworks, IEEE

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:25.290146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ab0f0b47-165d-4a87-ba2b-9f79251422b3 · outbound

This paper cites An acceleratorarchitectureforcombinatorialoptimizationproblems.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing An acceleratorarchitectureforcombinatorialoptimizationproblems

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:25.198924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1d00eb59-724b-4f78-ac7f-17f2917c8209 · outbound

This paper cites Clip-q:Deepnetworkcompressionlearning by in-parallel pruning-quantization, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Clip-q:Deepnetworkcompressionlearning by in-parallel pruning-quantization, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:25.070210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a829c5c0-c433-4f51-9991-dfbdc6cc658b · outbound

This paper cites Graph partitioning using quantum annealing on the d-wave system, in:ProceedingsoftheSecondInternationalWorkshoponPostMoores Era Supercomputing, pp.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Graph partitioning using quantum annealing on the d-wave system, in:ProceedingsoftheSecondInternationalWorkshoponPostMoores Era Supercomputing, pp

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:24.994766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1fe11520-b17f-489b-95a2-9b1395ae87c5 · outbound

This paper cites Edcompress: Energy-aware model compression for dataflows.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Edcompress: Energy-aware model compression for dataflows

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:24.919643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e77a8184-be45-4a96-988f-34b664ff7e5e · outbound

This paper cites Evolutionarymulti-objectivemodelcompressionfordeepneuralnet- works.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Evolutionarymulti-objectivemodelcompressionfordeepneuralnet- works

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:24.792290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 65098c00-d3a9-4b6c-8fa7-7e2fa3d13d28 · outbound

This paper cites an unresolved cited work.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:07:24.714914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation af77593b-ab46-42a4-8b93-6dcb425ddf95 · outbound

This paper cites Adiabatic quantum computing for multi object tracking, in: Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Adiabatic quantum computing for multi object tracking, in: Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:24.613091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b59061d8-afd7-41b6-b0f3-73f3b05901db · outbound

This paper cites To prune, or not to prune: exploring the efficacy of pruning for model compression.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing To prune, or not to prune: exploring the efficacy of pruning for model compression

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:24.333596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d45d0dfb-ad39-4a95-9d2f-61cb4908cbb9 · outbound

This paper cites borealis—a generalized global update algorithm for boolean optimization problems.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing borealis—a generalized global update algorithm for boolean optimization problems

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:24.491398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.