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Paper Citation Record · LEDGER

A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2308.06767.

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

pith.paper-citation-record.v1
2308.06767 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:52:37.710746Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

23
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2accfe90-169e-4d53-bff5-aa7d6e7343ed · inbound

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps cites this paper.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T18:19:14.913510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:19:14.913510Z digest=sha256:2bb4f0bd826b7fd68c89af39721c4cab62614b273511af957c91edc947cd7eed

Observation 417d5f50-f9ad-4d88-8dc8-ec91f55bee7f · inbound

Preserving Deep Representations In One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework cites this paper.

Preserving Deep Representations In One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T11:20:38.079133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:20:38.079133Z digest=sha256:af36f1c7fcddd62db127ea1ce8e6d7038225c669e84c7d91992252a53adf686a

Observation dd3503d4-76fa-4785-9e83-52d619a677ea · inbound

Lightweight Multiplane Images Network for Real-Time Stereoscopic Conversion from Planar Video cites this paper.

Lightweight Multiplane Images Network for Real-Time Stereoscopic Conversion from Planar Video A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T22:50:55.772058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:50:55.772058Z digest=sha256:df0aa9a0bd134f0f146cbd7850e9e6f37d60aa47e7a06afc6a791adb908fb5fc

Observation 2dbac768-120c-48f6-8558-bc085c9c7a6b · inbound

Test-time Cost-and-Quality Controllable Arbitrary-Scale Super-Resolution with Variable Fourier Components cites this paper.

Test-time Cost-and-Quality Controllable Arbitrary-Scale Super-Resolution with Variable Fourier Components A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-11T20:43:05.695359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:43:05.695359Z digest=sha256:a13d2d69934722f364abb0a4e0b404a2c41d0ebc294634e064e420af9a93a19b

Observation 5be4b879-acd9-46c1-b073-d86f78a6a092 · inbound

A Comparative Study of Pruning Methods in Transformer-based Time Series Forecasting cites this paper.

A Comparative Study of Pruning Methods in Transformer-based Time Series Forecasting A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T13:41:20.875929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:41:20.875929Z digest=sha256:b7ede31b6c761a288a8d8c927d03dd44b65ebfff408f23ce2636dbc137edba3b

Observation e75b3578-4b9d-4fb7-9aa1-b401138ed245 · inbound

A Comparative Study of Pruning Methods in Transformer-based Time Series Forecasting cites this paper.

A Comparative Study of Pruning Methods in Transformer-based Time Series Forecasting A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T13:41:20.881608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:41:20.881608Z digest=sha256:bd62fe5c413b8fba3f1094f60ca6e62926f11b2a645ba6ce3224c96279d37c6e

Observation bb1b7e64-a9b1-416b-a933-fe397e38a3df · inbound

Towards Responsible Governing AI Proliferation cites this paper.

Towards Responsible Governing AI Proliferation A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-11T12:47:48.415959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:47:48.415959Z digest=sha256:b17899a8ac96af522327a426a58e82dea546da8ec18ca75371f058368209982a

Observation 07121399-3a8b-470f-b370-7ead0203ee2a · inbound

Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models cites this paper.

Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T11:36:01.241057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:36:01.241057Z digest=sha256:50d98871c88997cf7e69af561508f549aad80633ba99144d6588819a9d1de7c1

Observation f4d4d3ee-e2bf-4e73-a5c8-43de26b3d9a0 · inbound

Grokking vs. Learning: Same Features, Different Encodings cites this paper.

Grokking vs. Learning: Same Features, Different Encodings A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-09T14:44:27.010340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:44:27.010340Z digest=sha256:c941f9c607df953db7c586d91e3d39347534a894a0308b26cdbebcf6d74c45ee

Observation 9dc4b57c-54b9-48e4-a385-7d720e75e0b8 · inbound

Forget the Data and Fine-Tuning! Just Fold the Network to Compress cites this paper.

Forget the Data and Fine-Tuning! Just Fold the Network to Compress A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T19:04:45.499512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T19:04:45.499512Z digest=sha256:1bb25f52ae712bb279d6ac8010461bd085fb7db38cd363fb23a75575a09b7003

Observation cc82b7a3-0d96-4e1a-9afb-55e7c7dfc299 · inbound

Hardware/Software Co-Design of RISC-V Extensions for Accelerating Sparse DNNs on FPGAs cites this paper.

Hardware/Software Co-Design of RISC-V Extensions for Accelerating Sparse DNNs on FPGAs A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-16T05:52:37.710746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:52:37.710746Z digest=sha256:e8010e5672cfcf229c9b17cc18b5726c979f75c7dc4e144ecbbe561abdfe8c9f

Observation 35d5802c-841d-4b34-b42e-b042a4e4aa9c · inbound

Vanishing Contributions: A Unified Framework for Smooth and Iterative Model Compression cites this paper.

Vanishing Contributions: A Unified Framework for Smooth and Iterative Model Compression A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-18T08:41:08.027762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T08:38:52.367887Z digest=sha256:d135568dcc57a8900031eef302d8caea0d8da0749f694eaef165142bf5aea6fc

Observation 30b4fb0c-0755-4a82-bcac-3fcdb7c60651 · inbound

WIDE: Boosting Adaptive LLM Inference via Token-level Dynamic Width Pruning cites this paper.

WIDE: Boosting Adaptive LLM Inference via Token-level Dynamic Width Pruning A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-07-31T08:00:55.931442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T08:00:55.931442Z digest=sha256:460ba760505f494525597260ae62cbfb6ed01a83855f5e2f5883c0a16f277c97