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Paper Citation Record · LEDGER

Topograph: An efficient Graph-Based Framework for Strictly Topology Preserving Image Segmentation

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.03228.

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

pith.paper-citation-record.v1
2411.03228 v2

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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:07:33.602563Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T11:45:32.849566Z

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 15e1e137-68df-4567-aecf-6a5dc090f4fd · inbound

Pitfalls of topology-aware image segmentation cites this paper.

Pitfalls of topology-aware image segmentation Topograph: An efficient Graph-Based Framework for Strictly Topology Preserving Image Segmentation

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T12:07:33.602563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:07:33.602563Z digest=sha256:5bbd7b4d17b7037ce08ea154df69f0f2d7f5560cc894a5bf16a8b92c8035d4ca

Observation ee0c70f2-fbaf-4876-9e16-60eb3f5131c2 · inbound

Topo-R1: Detecting Topological Anomalies via Vision-Language Models cites this paper.

Topo-R1: Detecting Topological Anomalies via Vision-Language Models Topograph: An efficient Graph-Based Framework for Strictly Topology Preserving Image Segmentation

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-05-15T11:45:32.851175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T11:41:27.021776Z digest=sha256:42f68395a34410547abcc57f3a8ac341923c4d1b8b2d57ce0532541f5166fe5a