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Paper Citation Record · LEDGER

Exploiting GPT-4 Vision for Zero-shot Point Cloud Understanding

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.07572.

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

pith.paper-citation-record.v1
2401.07572 v1

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T05:41:50.671046Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:26:56.823211Z

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 ff7cfef0-1306-4d11-8f5b-50b13af3fde6 · inbound

Geometry-Aware Dataset Condensation for Diffusion Model Training cites this paper.

Geometry-Aware Dataset Condensation for Diffusion Model Training Exploiting GPT-4 Vision for Zero-shot Point Cloud Understanding

Reference 88

Resolution
verified exact
arxiv_id, observed 2026-07-02T12:26:56.824546Z

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=arxiv_source observed=2026-06-28T02:07:54.718436Z digest=sha256:52627a72ce76f96a419f17a30c23ce1192bd2665f7eb9e10b87182e614340ed5

Observation bb6ea5cd-ab8a-41ea-a691-59a47c9f9d10 · inbound

Harnessing Generative Image Models for Training-Free Primitive Shape Abstraction cites this paper.

Harnessing Generative Image Models for Training-Free Primitive Shape Abstraction Exploiting GPT-4 Vision for Zero-shot Point Cloud Understanding

Reference 31

Resolution
unresolved
no resolver link, observed 2026-07-11T05:41:50.671046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T05:41:50.671046Z digest=sha256:9a1196b1f926e2852d865c9aef328b621a2ce7c8991389b340863891b3a44cd1