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Paper Citation Record · LEDGER

Hyperbolic Vision Transformers: Combining Improvements in Metric Learning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2203.10833.

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

pith.paper-citation-record.v1
2203.10833 v2

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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:05:58.962586Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation dfc756dd-51f1-40f4-b3f2-cd4206a7dcb3 · inbound

A Few-Shot Metric Learning Method with Dual-Channel Attention for Cross-Modal Same-Neuron Identification cites this paper.

A Few-Shot Metric Learning Method with Dual-Channel Attention for Cross-Modal Same-Neuron Identification Hyperbolic Vision Transformers: Combining Improvements in Metric Learning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-16T11:05:58.962586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:05:58.962586Z digest=sha256:2b32342b089561f6400e50261e541f3a4b99a5f8f5029b86aadf086c251cc202

Observation d969e7ce-6851-4687-9242-76ee26918994 · inbound

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering cites this paper.

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering Hyperbolic Vision Transformers: Combining Improvements in Metric Learning

Reference 226

Resolution
verified exact
arxiv_id, observed 2026-05-09T23:54:45.615277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-09T23:51:47.724033Z digest=sha256:49c79093b144cf412eb82d97a9e458402d3efd591b0ca7367b7e52c4cb700680