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Paper Citation Record · LEDGER

TransFG: A Transformer Architecture for Fine-grained Recognition

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2103.07976.

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

pith.paper-citation-record.v1
2103.07976 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:08:09.236675Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T12:45:29.473012Z

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 6ecf779e-df84-4e86-94a3-0e3bfc9bc4e4 · inbound

Navigating limitations with precision: A fine-grained ensemble approach to wrist pathology recognition on a limited x-ray dataset cites this paper.

Navigating limitations with precision: A fine-grained ensemble approach to wrist pathology recognition on a limited x-ray dataset TransFG: A Transformer Architecture for Fine-grained Recognition

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-11T12:45:29.480106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T12:45:29.333464Z digest=sha256:0c4285fed4eaf58c49691e294059b10560c07b2cf910b16310fea01db65bd005

Observation b71b7408-3c1a-49d3-809c-c2845f9af2a1 · inbound

Advancing Image-Based Grapevine Variety Classification with a New Benchmark and Evaluation of Masked Autoencoders cites this paper.

Advancing Image-Based Grapevine Variety Classification with a New Benchmark and Evaluation of Masked Autoencoders TransFG: A Transformer Architecture for Fine-grained Recognition

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T20:08:09.236675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:08:09.236675Z digest=sha256:900c596a30d2c1a4623972be77639de884e5b55e12aecd4d87c953b74dec37a1