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Paper Citation Record · LEDGER

PerceptionGPT: Effectively Fusing Visual Perception into LLM

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.06612.

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

pith.paper-citation-record.v1
2311.06612 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 2026-08-06T17:22:12.222475Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T15:36:34.000271Z

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 ac7378b4-d987-40b7-aad6-4158d99f5e3e · inbound

KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model cites this paper.

KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model PerceptionGPT: Effectively Fusing Visual Perception into LLM

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T17:22:12.222475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:22:12.222475Z digest=sha256:1d9c6ff0f1c0e6a37ecf919b24e1abaa633aaf1d49aba956a0e2411eeff943bc

Observation 3b47eeb7-b1f4-4a4e-9041-6258a3ec5da0 · inbound

MINGLE: VLMs for Semantically Complex Region Detection in Urban Scenes cites this paper.

MINGLE: VLMs for Semantically Complex Region Detection in Urban Scenes PerceptionGPT: Effectively Fusing Visual Perception into LLM

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-18T15:36:34.003208Z

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=pdf_text observed=2026-05-18T15:35:30.549656Z digest=sha256:32932aea4c342a433aa1ecfc8a90e483afdcc481c19a860ae44ec5a23c4f460e