Paper Citation Record · LEDGER

A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2112.00639.

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

pith.paper-citation-record.v1
2112.00639 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:03:55.417106Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T22:45:50.832131Z

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 c24ac485-d681-4290-8a3e-3b47dcea4466 · inbound

SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge cites this paper.

SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-23T22:45:50.834657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b8e79915-b529-4624-bef2-114a8d6db8d1 · inbound

From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models cites this paper.

From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:03:55.417106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58327f5b-0eb2-447a-baf6-baad496eb1de · inbound

Same Compression Principle, Different Geometry: Rate-Distortion Signatures Dissociate Biological and Artificial Visual Systems cites this paper.

Same Compression Principle, Different Geometry: Rate-Distortion Signatures Dissociate Biological and Artificial Visual Systems A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T19:40:44.400400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f3e07de-1788-4354-a18a-686fd95e1b4e · inbound

Advancing Trustworthy AI in Healthcare Through Meta-Research: Results of an Interdisciplinary Design-Thinking Workshop cites this paper.

Advancing Trustworthy AI in Healthcare Through Meta-Research: Results of an Interdisciplinary Design-Thinking Workshop A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-15T17:56:24.876148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6f360529-f7b8-4db6-96d2-3218741c171b · inbound

Stress-Testing Neural Network Verifiers with Provably Robust Instances cites this paper.

Stress-Testing Neural Network Verifiers with Provably Robust Instances A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:53:23.463087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.