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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 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 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:54:26.828151Z

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T22:44:36.339252Z digest=sha256:505ed1062abf4687c9cd91fa7aad7aeaea8eafa6f56cc318a22864ed293c81e5

Observation b485b7bc-842c-4efb-8981-29abf5baed1f · inbound

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks cites this paper.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-08T12:54:26.828151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:54:26.828151Z digest=sha256:7c23cde422a140e5f2bfd86ecc1e954c77fbf07f9fc5095c731d4fb66d1a6238

Observation b5622532-931e-4207-8370-9a48c0e86930 · inbound

Towards Virtual Clinical Trials of Radiology AI with Conditional Generative Modeling cites this paper.

Towards Virtual Clinical Trials of Radiology AI with Conditional Generative Modeling A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T21:34:57.298471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:34:57.298471Z digest=sha256:39dcc3c3376f023a673d3be2ac844a9cd2fb7c71ee0848d3ae9958d83f05db82

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.

source=pdf_text observed=2026-08-07T12:03:55.417106Z digest=sha256:922983b0bc9aec3dc92279bc24d0cd566a73ce685c23a46ad2a77c5ef46c40db

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.

source=arxiv_source observed=2026-08-02T19:40:44.400400Z digest=sha256:9559be93ceb4e94dbfaf27b40ad9e2fe7279031b3ee470a9e81f1803cf49a7af

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T17:55:39.736751Z digest=sha256:05122303819c417781454044de63d56b9828a13d570d89481c46dae07e0e9ddf

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T14:48:54.688641Z digest=sha256:91ecbf199539187045dedc62278c0379b6f5c48ce0a9168938680d9293714e56