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Paper Citation Record · LEDGER

Towards Training-free Open-world Segmentation via Image Prompt Foundation Models

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.10912.

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

pith.paper-citation-record.v1
2310.10912 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T07:43:28.627414Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T07:44:02.779606Z

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 57700782-acae-40ef-9371-bf30f33be7e9 · inbound

SegRAG: Training-Free Retrieval-Augmented Semantic Segmentation cites this paper.

SegRAG: Training-Free Retrieval-Augmented Semantic Segmentation Towards Training-free Open-world Segmentation via Image Prompt Foundation Models

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:53:19.899298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-20T13:51:35.769341Z digest=sha256:700f2c38816a837580e0aa2bca58875883dcf2e8c405f76e0b3405bf8fa9a9f6

Observation e26a1147-db22-482d-b825-ce23267b615f · inbound

SegRAG: Training-Free Retrieval-Augmented Semantic Segmentation cites this paper.

SegRAG: Training-Free Retrieval-Augmented Semantic Segmentation Towards Training-free Open-world Segmentation via Image Prompt Foundation Models

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-21T07:44:02.781011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-21T07:43:28.627414Z digest=sha256:e9fa32d89692fed2fe1a41db3acebb74ef513652a5033b18857a4771aad18778