Paper Citation Record · LEDGER

Testing Deep Neural Networks

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1803.04792.

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

pith.paper-citation-record.v1
1803.04792 v4

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 2026-08-21T06:32:19.484+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:15:54.435030Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-25T19:01:09.301384Z

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 0a382148-24b7-4e7a-97eb-ccb9b37dde91 · inbound

testRNN: Coverage-guided Testing on Recurrent Neural Networks cites this paper.

testRNN: Coverage-guided Testing on Recurrent Neural Networks Testing Deep Neural Networks

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:01:09.303882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7c8e6e19-48e0-4ded-a222-4b634d5068ff · inbound

Detecting Deep Neural Network Defects with Data Flow Analysis cites this paper.

Detecting Deep Neural Network Defects with Data Flow Analysis Testing Deep Neural Networks

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-14T05:01:18.252388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb3e146f-69b7-4961-a01e-5c93c4577707 · inbound

Data Sanity Check for Deep Learning Systems via Learnt Assertions cites this paper.

Data Sanity Check for Deep Learning Systems via Learnt Assertions Testing Deep Neural Networks

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-14T04:41:20.522035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccd6c7c5-1c37-4779-920a-0a316c0c148f · inbound

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test cites this paper.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Testing Deep Neural Networks

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.172376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f94ad94-20dc-4bc6-8418-7d0ddaf4dc5c · inbound

A Topological Improvement of the Overall Performance of Sparse Evolutionary Training: Motif-Based Structural Optimization of Sparse MLPs Project cites this paper.

A Topological Improvement of the Overall Performance of Sparse Evolutionary Training: Motif-Based Structural Optimization of Sparse MLPs Project Testing Deep Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T04:59:48.987403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6e50408-896d-4bcf-82be-e0c910bf37c7 · inbound

Influence-Guided Concolic Testing of Transformer Robustness cites this paper.

Influence-Guided Concolic Testing of Transformer Robustness Testing Deep Neural Networks

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:52.195297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dbb0ee7-a58c-4bd9-9094-3b82536d2f74 · inbound

ADEPT: A Unified Framework for Deep Learning Test Adequacy cites this paper.

ADEPT: A Unified Framework for Deep Learning Test Adequacy Testing Deep Neural Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T00:15:54.435030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.