Paper Citation Record · LEDGER

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks

As of 20 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:1908.04471.

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

pith.paper-citation-record.v1
1908.04471 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:46:22.105774Z

measured 15 of 15 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 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

15 of 15 outbound references displayed

verified exact2
verified fuzzy1
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69145c3a-4f38-4bc6-a771-6ea50eac3128 · outbound

This paper cites Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.045277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42829325-5383-4706-b4e0-d83184bf5f4d · outbound

This paper cites Resource Efficient 3D Convolutional Neural Networks.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Resource Efficient 3D Convolutional Neural Networks

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-14T13:46:22.284181Z

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 ae573050-aceb-47ef-a228-8b03bc72ce7a · outbound

This paper cites Learning Spatiotemporal Features with 3D Convolutional Networks.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Learning Spatiotemporal Features with 3D Convolutional Networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.089296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f055bc8-0586-491b-9f03-edbef328dcab · outbound

This paper cites an unresolved cited work.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:46:22.376037Z

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 66d4ef87-fd63-4e96-a526-1edbd483a50c · outbound

This paper cites Tensor network ranks.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Tensor network ranks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.100230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28e591bb-80fd-43f9-9037-34388934859e · outbound

This paper cites Neural Architecture Search with Reinforcement Learning.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Neural Architecture Search with Reinforcement Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.105774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0507197b-ca81-4610-887e-0a8ca9150630 · outbound

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

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 1927

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.038871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b482b8a0-2b4f-49bf-9b56-1f02d79876e8 · outbound

This paper cites Efficient Neural Architecture Search via Parameter Sharing.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Efficient Neural Architecture Search via Parameter Sharing

Reference 1971

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.067721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f56c177a-2094-46a7-9304-c73a48612423 · outbound

This paper cites Network In Network.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Network In Network

Reference 1998

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.061773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8d500b8-b8c9-4241-9b08-b925a4af442e · outbound

This paper cites Convergence of iterated Aluthge transform sequence for diagonalizable matrices II: $\lambda$-Aluthge transform.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Convergence of iterated Aluthge transform sequence for diagonalizable matrices II: $\lambda$-Aluthge transform

Reference 2009

Resolution: verified exact; local_arxiv, observed 2026-08-14T13:46:22.341079Z

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 f6d55a51-5f8a-4463-93e2-40659829fc40 · outbound

This paper cites Tokui, R.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Tokui, R

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:46:22.392471Z

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 fb640d3a-7167-4464-bdbe-1463682d8ed2 · outbound

This paper cites Convolutional neural networks with low-rank regularization.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Convolutional neural networks with low-rank regularization

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.078212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d508852-720b-4bcc-b0be-86abbea96353 · outbound

This paper cites Xception: Deep Learning with Depthwise Separable Convolutions.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Xception: Deep Learning with Depthwise Separable Convolutions

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.026944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbc53bfc-0c29-46ce-a475-b92e2e640d9d · outbound

This paper cites Regularized Evolution for Image Classifier Architecture Search.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Regularized Evolution for Image Classifier Architecture Search

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.072462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 891591b6-841f-4665-b32f-6db1017e7398 · outbound

This paper cites Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition.

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-14T13:46:22.056363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.