Paper Citation Record · LEDGER

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices

As of 20 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:1909.05073.

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

pith.paper-citation-record.v1
1909.05073 v4

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:48:18.582366Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-24T16:18:13.178018Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T16:19:40.208307Z

Reference resolution

12 of 12 outbound references displayed

verified exact0
verified fuzzy6
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fbc58b9a-18a3-4a1b-aff1-5e5a062bc2bb · outbound

This paper cites In Computer Vision (ICCV), 2017 IEEE International Conference on, 1398–1406.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices In Computer Vision (ICCV), 2017 IEEE International Conference on, 1398–1406

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:48:18.825446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c62b0783-0ad9-4aa7-bb78-a5e4cafa6578 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T04:48:18.539116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1172ecf0-f229-4bef-93e8-91c2a2ed2c1d · outbound

This paper cites Exploring the Regularity of Sparse Structure in Convolutional Neural Networks.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices Exploring the Regularity of Sparse Structure in Convolutional Neural Networks

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-08-14T04:48:18.646168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 104113ad-d11d-4f06-bdfe-079af0644a2f · outbound

This paper cites In Computer Vision (ICCV), 2019 IEEE International Conference on.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices In Computer Vision (ICCV), 2019 IEEE International Conference on

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:48:18.789159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e3bd1d7f-cd54-4cf1-ad69-979b5e9e9ded · outbound

This paper cites In ICLR-2015 workshop track.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices In ICLR-2015 workshop track

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:48:18.754191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57a14a19-8cce-40b7-a5b0-56a5b9b4d2c7 · outbound

This paper cites In Advances in neural information processing systems, 2074–2082.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices In Advances in neural information processing systems, 2074–2082

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:48:18.736400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation efdf02b4-b275-46aa-b4b8-db18583e1b68 · outbound

This paper cites In 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems, 460–469.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices In 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems, 460–469

Reference 2011

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:48:18.806471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 85173294-c871-4805-ab8b-4c20648423ce · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-14T04:48:18.566889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c75afc7d-6730-4230-bccf-b1dee5e70337 · outbound

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

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-14T04:48:18.528531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bdc64d6-e702-466f-b1e1-f5abdadbb574 · outbound

This paper cites Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-14T04:48:18.544912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8a07780-24f0-4b91-8e42-60860ce418bc · outbound

This paper cites NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm

Reference 2017

Resolution: metadata mismatch; local_arxiv, observed 2026-08-14T04:48:18.719448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e0d7f4e-28c0-4562-b0e4-44ca49ab8e58 · outbound

This paper cites In 2018 International Conference on Ma- chine Learning (ICML).

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices In 2018 International Conference on Ma- chine Learning (ICML)

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:48:18.771963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 849749a3-2905-4466-a6ab-00412ba05701 · inbound

Neural Network Training with Approximate Logarithmic Computations cites this paper.

Neural Network Training with Approximate Logarithmic Computations PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-24T16:19:40.211650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.