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Paper Citation Record · LEDGER

Fully Hyperbolic Convolutional Neural Networks for Computer Vision

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2303.15919.

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

pith.paper-citation-record.v1
2303.15919 v3

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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:58:55.201236Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T10:24:25.784966Z

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 7f5342ab-2ec3-4aa0-b7ab-56557d13cbb4 · inbound

Even Faster Hyperbolic Random Forests: A Beltrami-Klein Wrapper Approach cites this paper.

Even Faster Hyperbolic Random Forests: A Beltrami-Klein Wrapper Approach Fully Hyperbolic Convolutional Neural Networks for Computer Vision

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T10:58:55.201236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:58:55.201236Z digest=sha256:e615564f0c3717b4176ec8cca570bc3699b7f8e574aaab78637b264b486b82ee

Observation 241fe005-d6fb-4e0a-976f-7ec839e7280d · inbound

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning cites this paper.

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning Fully Hyperbolic Convolutional Neural Networks for Computer Vision

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:24:25.791074Z

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=arxiv_source observed=2026-08-07T10:24:23.749133Z digest=sha256:7672d48a9b5238403808daf52686ed3c0c4d7df851559ef28b44d2e0cdeff8a8