Paper Citation Record · LEDGER

Compressing Deep Neural Networks Using Explainable AI

As of 9 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2507.05286.

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

pith.paper-citation-record.v1
2507.05286 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:07:21.282552Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

25 of 25 outbound references displayed

verified exact1
verified fuzzy23
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d52b6d93-f31a-46f0-8c16-5ca93fbd4485 · outbound

This paper cites ECQ: Explainability -Driven Quantization for Low-Bit and Sparse DNNs.

Compressing Deep Neural Networks Using Explainable AI ECQ: Explainability -Driven Quantization for Low-Bit and Sparse DNNs

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:24.952242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ad1a7c3a-404e-4167-913c-1ba9ed091e27 · outbound

This paper cites Pruning by explaining: A nove l criterion for deep neural network pruning.

Compressing Deep Neural Networks Using Explainable AI Pruning by explaining: A nove l criterion for deep neural network pruning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:24.838339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 877ac820-9740-4121-bbbc-472f7af94b15 · outbound

This paper cites Utilizing Explainable AI for Quantization and Pruning of Deep Neural Networks.

Compressing Deep Neural Networks Using Explainable AI Utilizing Explainable AI for Quantization and Pruning of Deep Neural Networks

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-06T20:07:21.398680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e2c74b5b-c672-4e33-a06e-9631f51b15de · outbound

This paper cites Explaining deep neural networks and beyond: A review of methods and applications.

Compressing Deep Neural Networks Using Explainable AI Explaining deep neural networks and beyond: A review of methods and applications

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:24.701897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 431d8b79-d897-4a04-acb9-089d66a2fb12 · outbound

This paper cites Layer -wise relevance propagation: an overview.

Compressing Deep Neural Networks Using Explainable AI Layer -wise relevance propagation: an overview

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:24.621418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6cb7634f-b4b9-449b-a7c9-306c506b1c15 · outbound

This paper cites Learning important features through propagating activation differences.

Compressing Deep Neural Networks Using Explainable AI Learning important features through propagating activation differences

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:24.503217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cbcdbfb5-e6ad-403e-a204-12a8a9e97e8b · outbound

This paper cites Model compression and hardware acceleration for neural networks: A comprehensive survey.

Compressing Deep Neural Networks Using Explainable AI Model compression and hardware acceleration for neural networks: A comprehensive survey

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:24.370411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1ed04a62-f6eb-4951-9a4a-f435ae6d9215 · outbound

This paper cites Pruning convolutional neural networks for resource efficient inference.

Compressing Deep Neural Networks Using Explainable AI Pruning convolutional neural networks for resource efficient inference

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:24.219235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3768d9ed-377f-4622-991c-cdc47cfb76fe · outbound

This paper cites Channel pruning based on mean gradient for accelerating convolutional neural networks.

Compressing Deep Neural Networks Using Explainable AI Channel pruning based on mean gradient for accelerating convolutional neural networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:24.055220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 91dba905-a6f5-4168-8e43-c2fea78f7079 · outbound

This paper cites Nisp: Pruning networks using neuron importance score propagation.

Compressing Deep Neural Networks Using Explainable AI Nisp: Pruning networks using neuron importance score propagation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:23.889749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3bb0a40f-3087-46ed-b789-3f33751b9317 · outbound

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

Compressing Deep Neural Networks Using Explainable AI Pruning and quantization for deep neural network acceleration: A survey

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:23.782464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 82ab1a0b-ffb0-4ee5-833e-46e1939ec950 · outbound

This paper cites Convolutional neural network pruning: A survey.

Compressing Deep Neural Networks Using Explainable AI Convolutional neural network pruning: A survey

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:23.626768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b11afe67-ed29-4c0d-8630-39d667ca622b · outbound

This paper cites Quantizing deep convolutional networks for efficient inference: A whitepaper.

Compressing Deep Neural Networks Using Explainable AI Quantizing deep convolutional networks for efficient inference: A whitepaper

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T20:07:20.973675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d8ae562-1658-453e-814f-5ee04517a3f5 · outbound

This paper cites Automatic pruning for quantized neural networks.

Compressing Deep Neural Networks Using Explainable AI Automatic pruning for quantized neural networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:23.491081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a6ea76e3-04e5-4c05-a173-f80f9f91e86f · outbound

This paper cites Model compression and hardware acceleration for neural networks: A comprehensive survey.

Compressing Deep Neural Networks Using Explainable AI Model compression and hardware acceleration for neural networks: A comprehensive survey

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:23.360394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5f50cb74-6a87-49f8-8f2c-147153d97f2d · outbound

This paper cites Autocompress: An automatic dnn structured pruning framework for ultra -high compression rates.

Compressing Deep Neural Networks Using Explainable AI Autocompress: An automatic dnn structured pruning framework for ultra -high compression rates

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:23.228228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a2eb06b2-6567-470a-bc6a-53046f7a3d46 · outbound

This paper cites Clip -q: Deep network compression learning by in -parallel pruning -quantization.

Compressing Deep Neural Networks Using Explainable AI Clip -q: Deep network compression learning by in -parallel pruning -quantization

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:23.070655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation eb5bc80e-a825-4fbd-9a3b-8d27170c842c · outbound

This paper cites Admm-nn: An algorithm-hardware co-design framework of dnns using alternating direction methods of multipliers.

Compressing Deep Neural Networks Using Explainable AI Admm-nn: An algorithm-hardware co-design framework of dnns using alternating direction methods of multipliers

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:22.966754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 046a57b6-e300-464d-9d64-5a9432293a98 · outbound

This paper cites Automatic neural network compression by sparsity-quantization joint learning: A constrained optimization -based ap proach.

Compressing Deep Neural Networks Using Explainable AI Automatic neural network compression by sparsity-quantization joint learning: A constrained optimization -based ap proach

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:22.736717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 339301de-4a59-49cb-a39a-a29a45110f2b · outbound

This paper cites Accelerator -aware pruning for convolutional neural networks.

Compressing Deep Neural Networks Using Explainable AI Accelerator -aware pruning for convolutional neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:22.580524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 911092af-31ab-4325-9879-48e0e8ba92bb · outbound

This paper cites Optimal brain compression: A framework for accurate post -training quantization and pruning.

Compressing Deep Neural Networks Using Explainable AI Optimal brain compression: A framework for accurate post -training quantization and pruning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:22.428965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1ed5d2bd-1339-4ae0-85ad-9dc347098ccb · outbound

This paper cites Nisp: Pru ning networks using neuron importance score propagation.

Compressing Deep Neural Networks Using Explainable AI Nisp: Pru ning networks using neuron importance score propagation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:22.325951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 58fbabf0-37af-4804-ab55-d5af10582624 · outbound

This paper cites Thinet: pruning cnn filters for a thinner net.

Compressing Deep Neural Networks Using Explainable AI Thinet: pruning cnn filters for a thinner net

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:22.161294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 934a8c9e-886f-4f8b-bf59-50808952be73 · outbound

This paper cites Compressing the CNN architecture for in -air handwritten Chinese character recognition.

Compressing Deep Neural Networks Using Explainable AI Compressing the CNN architecture for in -air handwritten Chinese character recognition

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:21.999322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 448acd48-8877-4a53-a01f-d9c56eaa7e89 · outbound

This paper cites NeST: A neural network synthesis tool based on a grow -and-prune paradigm.

Compressing Deep Neural Networks Using Explainable AI NeST: A neural network synthesis tool based on a grow -and-prune paradigm

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:21.561653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.