Paper Citation Record · LEDGER

Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1808.06866.

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

pith.paper-citation-record.v1
1808.06866 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:44:07.585567Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T10:19:04.519943Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7935c2bd-7dba-4c92-9498-d0236e17db73 · inbound

prunAdag: an adaptive pruning-aware gradient method cites this paper.

prunAdag: an adaptive pruning-aware gradient method Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T05:44:07.585567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01b501f4-a183-41fd-bdef-54057fda7cd4 · inbound

Structured Pruning and Quantization for Learned Image Compression cites this paper.

Structured Pruning and Quantization for Learned Image Compression Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T11:51:37.752820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ccd63ad-7094-4589-915c-cd4001a9217e · inbound

Efficient Test-time Adaptive Object Detection via Sensitivity-Guided Pruning cites this paper.

Efficient Test-time Adaptive Object Detection via Sensitivity-Guided Pruning Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T11:28:22.503519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99a7f68d-6783-4555-b17d-4b90287a939b · inbound

Loss-Aware Automatic Selection of Structured Pruning Criteria for Deep Neural Network Acceleration cites this paper.

Loss-Aware Automatic Selection of Structured Pruning Criteria for Deep Neural Network Acceleration Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:46.669524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a66c0dd6-5109-40c1-aabc-e80d3bdc2481 · inbound

Towards Universal & Efficient Model Compression via Exponential Torque Pruning cites this paper.

Towards Universal & Efficient Model Compression via Exponential Torque Pruning Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-06T22:17:43.047924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acd5db23-ac30-45a2-b364-543a7363590d · inbound

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models cites this paper.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:28.017036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6f46192-6141-459c-bcdb-f3b851daddb7 · inbound

Integrating Pruning with Quantization for Efficient Deep Neural Networks Compression cites this paper.

Integrating Pruning with Quantization for Efficient Deep Neural Networks Compression Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:04.526135Z

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 fc47109e-0e18-4fc4-86fa-57c859a55369 · inbound

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning cites this paper.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T10:19:22.874589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cfad0e5-2342-4c00-b82d-ca068bac789f · inbound

PrivDNN: A Secure Multi-Party Computation Framework for Deep Learning using Partial DNN Encryption cites this paper.

PrivDNN: A Secure Multi-Party Computation Framework for Deep Learning using Partial DNN Encryption Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-01T06:31:08.856358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.