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Paper Citation Record · LEDGER

Comprehensive Pathological Image Segmentation via Teacher Aggregation for Tumor Microenvironment Analysis

As of 15 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 0 inbound Pith citation observations for arXiv:2501.02909.

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

pith.paper-citation-record.v1
2501.02909 v1

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:07:39.443444Z

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

2 of 2 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b02ca529-1d51-491d-9035-3d60c8268158 · outbound

This paper cites PanNuke Dataset Extension, Insights and Baselines.

Comprehensive Pathological Image Segmentation via Teacher Aggregation for Tumor Microenvironment Analysis PanNuke Dataset Extension, Insights and Baselines

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T22:07:39.420644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:39.420644Z digest=sha256:34deef01a26f9c592e1187c7973e4bdfc0159bfefc584def3f51f35c2ae488cb

Observation 3033f18f-9c50-4398-9adf-2f6a4fda8284 · outbound

This paper cites SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers.

Comprehensive Pathological Image Segmentation via Teacher Aggregation for Tumor Microenvironment Analysis SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T22:07:39.443444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:39.443444Z digest=sha256:178b963e226b6dea79104231d17e0c18002a2dc0bd6d2536cb8f909efeeec6e3

Pith citing papers

No inbound Pith citation observations are available.