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Paper Citation Record · LEDGER

Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentation

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.17859.

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

pith.paper-citation-record.v1
2405.17859 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 2026-08-03T06:30:56.289259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T21:20:18.079969Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T15:08:32.905507Z

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 f87b17e7-1c74-40ef-8336-20a0a5e2e2b8 · inbound

CAD-Prompted SAM3: Geometry-Conditioned Instance Segmentation for Industrial Objects cites this paper.

CAD-Prompted SAM3: Geometry-Conditioned Instance Segmentation for Industrial Objects Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-02T21:20:18.079969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:20:18.079969Z digest=sha256:84e457fbcacf5333480fd9d95c5b5e2ab61839f9790bbf701ae3a7d8f1ed4f80

Observation c6c43ce7-6622-48ba-8ace-8c3827e83a0e · inbound

Towards Reliable Sequential Object Picking in Clutter: The Runner-up Solution to RGMC 2025 cites this paper.

Towards Reliable Sequential Object Picking in Clutter: The Runner-up Solution to RGMC 2025 Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentation

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-03T15:08:32.907527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-06-27T06:42:00.660427Z digest=sha256:5914423a2691ae116dc9a409ea58fe8501189c6d2f3d2428d69c65648c3bb58e