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Paper Citation Record · LEDGER

Intriguing Properties of Vision Transformers

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2105.10497.

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

pith.paper-citation-record.v1
2105.10497 v3

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 2026-08-05T19:22:22.766573Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T21:18:58.635235Z

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 18dbadf6-4285-48fb-8461-d83f0081ab39 · inbound

iBOT: Image BERT Pre-Training with Online Tokenizer cites this paper.

iBOT: Image BERT Pre-Training with Online Tokenizer Intriguing Properties of Vision Transformers

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-14T02:10:27.606729Z

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.

source=pdf_text observed=2026-05-14T02:10:27.569787Z digest=sha256:d03a1a48fd5b9abd65b1c25803813b7783a1ec247d82f618b095d31ba39be32d

Observation 46ac8727-8e2d-47ba-b0dc-da2f0e621c86 · inbound

Morphological classification of eclipsing binary stars using computer vision methods cites this paper.

Morphological classification of eclipsing binary stars using computer vision methods Intriguing Properties of Vision Transformers

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T19:22:22.766573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:22:22.766573Z digest=sha256:13d1152d438dea58b9e4d8edc36d65cf83388a0f45f373e31b3f627b8d12b097

Observation d2e73924-eccd-458b-965d-c833864ba496 · inbound

Beyond Compression: Quantifying Spectral Accessibility in Vision Representations cites this paper.

Beyond Compression: Quantifying Spectral Accessibility in Vision Representations Intriguing Properties of Vision Transformers

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:46:27.721428Z

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.

source=pdf_text observed=2026-06-28T10:44:16.896069Z digest=sha256:f7c1e1db5f792e432cf9731bc1ddeb770b4ba782954c91bff811a9d221247ebc

Observation 6fa2bb85-a10b-43ce-b67a-dae07f158ba4 · inbound

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks cites this paper.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Intriguing Properties of Vision Transformers

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-03T21:18:58.636654Z

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.

source=pdf_text observed=2026-06-27T00:45:33.196262Z digest=sha256:0fb09480b8581769225f5fa3b89d61a3f41cc0f4cbc4904bc0ffcefc4d2e7ac0

Observation c631b0c7-194a-4744-badb-bbda5c34b553 · inbound

OmniDS: Dual-Stream Context Fusion for Omnidirectional Depth from Fisheye Cameras cites this paper.

OmniDS: Dual-Stream Context Fusion for Omnidirectional Depth from Fisheye Cameras Intriguing Properties of Vision Transformers

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-12T05:17:21.435075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T05:17:21.435075Z digest=sha256:eba6fc69e150a9dfb247eb34d83f3428267f3af366448fb11ed110cd2fc3fc05