Paper Citation Record · LEDGER

Deeply-Supervised Nets

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1409.5185.

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

pith.paper-citation-record.v1
1409.5185 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:17:56.882787Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T23:56:05.686354Z

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 f8936eb7-a49f-40f4-8f31-a42f6fbb04a2 · inbound

Deep Residual Learning for Image Recognition cites this paper.

Deep Residual Learning for Image Recognition Deeply-Supervised Nets

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-04T21:54:22.867807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9e1a1514-7f9b-46cb-97cb-7a9fcbbf8f4e · inbound

Density estimation using Real NVP cites this paper.

Density estimation using Real NVP Deeply-Supervised Nets

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-04T21:54:22.867807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 89bf029b-7bf5-4324-88bc-1a1a85a43855 · inbound

Adaptive Regularization of Labels cites this paper.

Adaptive Regularization of Labels Deeply-Supervised Nets

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T13:17:56.882787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 361c98b7-8f68-4fd8-843a-bd56045ad458 · inbound

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers cites this paper.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Deeply-Supervised Nets

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.869144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c49e856e-6f23-436b-8ac0-6ce32e916aec · inbound

fabSAM: A Farmland Boundary Delineation Method Based on the Segment Anything Model cites this paper.

fabSAM: A Farmland Boundary Delineation Method Based on the Segment Anything Model Deeply-Supervised Nets

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:07.629460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46eb3370-088f-4f22-9d3d-dd3e7193b5a0 · inbound

Supervised Extraction of the Thermal Sunyaev$-$Zel'dovich Effect with a Three-Dimensional Convolutional Neural Network cites this paper.

Supervised Extraction of the Thermal Sunyaev$-$Zel'dovich Effect with a Three-Dimensional Convolutional Neural Network Deeply-Supervised Nets

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T16:50:25.153232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d6d38a4-c6b0-453b-86ec-568794265d6f · inbound

Think Deep, Speak Once: Relit, A Recursive Latent Implicit Transformer Framework cites this paper.

Think Deep, Speak Once: Relit, A Recursive Latent Implicit Transformer Framework Deeply-Supervised Nets

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-12T00:29:44.599110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.