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Paper Citation Record · LEDGER

MetaFormer: A Unified Meta Framework for Fine-Grained Recognition

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2203.02751.

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

pith.paper-citation-record.v1
2203.02751 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:08:10.096234Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T23:59:06.684870Z

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 4aee11a0-378e-427d-8c87-2e7778edba08 · inbound

SGIA: Enhancing Fine-Grained Visual Classification with Sequence Generative Image Augmentation cites this paper.

SGIA: Enhancing Fine-Grained Visual Classification with Sequence Generative Image Augmentation MetaFormer: A Unified Meta Framework for Fine-Grained Recognition

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T20:01:22.090907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:01:22.090907Z digest=sha256:fdd48159e134f30c41d9b3058c570d6228d003c594de95b7661fd64f98af1149

Observation 1a8e6cce-844a-4e38-aa91-2c744cb7b2de · 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 MetaFormer: A Unified Meta Framework for Fine-Grained Recognition

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T12:45:29.337152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:45:29.337152Z digest=sha256:cb985b977842400ce375342805f8354096f5abab185c7443d0a9021912897093

Observation d08725f1-a90a-4288-bc8d-4e2ef57fda45 · inbound

Cross-Hierarchical Bidirectional Consistency Learning for Fine-Grained Visual Classification cites this paper.

Cross-Hierarchical Bidirectional Consistency Learning for Fine-Grained Visual Classification MetaFormer: A Unified Meta Framework for Fine-Grained Recognition

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-16T12:08:10.096234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:08:10.096234Z digest=sha256:3d33f1a4360a2e4f7a4cf26e7ac53ae23348648d94d96905cf371b1b71a0da73

Observation abaff31c-67ff-439a-b952-cd88f1f17d56 · inbound

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation cites this paper.

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation MetaFormer: A Unified Meta Framework for Fine-Grained Recognition

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-22T18:26:55.293122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-22T18:26:12.597756Z digest=sha256:4079f1797faca0d3a52abdd66551ec35c7f9f1b88adf8d8b9b6de2fb7d0ef404

Observation 888e151a-27bd-49ec-96a9-f40851156b63 · inbound

CrypticBio: A Large Multimodal Dataset for Visually Confusing Biodiversity cites this paper.

CrypticBio: A Large Multimodal Dataset for Visually Confusing Biodiversity MetaFormer: A Unified Meta Framework for Fine-Grained Recognition

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T20:59:35.559239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:59:35.559239Z digest=sha256:66f6bf8c813e3f8aac932e6e3eee3208a5ed9303450301de8afa6c3e22e03bc1

Observation 08a3ebc9-7a58-4978-a30a-21da477d183d · inbound

AquaMonitor: A multimodal multi-view image sequence dataset for real-life aquatic invertebrate biodiversity monitoring cites this paper.

AquaMonitor: A multimodal multi-view image sequence dataset for real-life aquatic invertebrate biodiversity monitoring MetaFormer: A Unified Meta Framework for Fine-Grained Recognition

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T13:19:27.180984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:19:27.180984Z digest=sha256:72f9029dfa268645904703f1a35112bb520646d05476822dcdaf42a58d1983d4

Observation 6a852324-5400-4325-aa1f-5a5393aab46e · inbound

Towards Continuous Home Cage Monitoring: An Evaluation of Tracking and Identification Strategies for Laboratory Mice cites this paper.

Towards Continuous Home Cage Monitoring: An Evaluation of Tracking and Identification Strategies for Laboratory Mice MetaFormer: A Unified Meta Framework for Fine-Grained Recognition

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T18:33:35.226751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:35.226751Z digest=sha256:a53e0bd0798ec0f80975d48cf6c639a7737dfe2f4f10c9adf6504e34c906ff53

Observation 7b7a3d1c-07cf-4289-b4a7-13b5e5b16a42 · inbound

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: From Evaluation to Diagnosis cites this paper.

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: From Evaluation to Diagnosis MetaFormer: A Unified Meta Framework for Fine-Grained Recognition

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-07-03T23:59:06.687859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-26T21:36:58.563495Z digest=sha256:1b0bc40e595b743281970252ed615c389337ef21bb0019c46ef7f8be34fad004