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Paper Citation Record · LEDGER

Revisiting MAE pre-training for 3D medical image segmentation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.23132.

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

pith.paper-citation-record.v1
2410.23132 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:11:30.157061Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:16:30.548575Z

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 d4472b95-db8f-453e-a79f-c3db81ca88be · inbound

General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound cites this paper.

General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound Revisiting MAE pre-training for 3D medical image segmentation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T23:11:30.157061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:11:30.157061Z digest=sha256:2cea40729ae4b6ebd3864c6482edc937290c31e6b4e7cf1d523b74efd2d9ff70

Observation 9ce6733d-47f1-4987-ab7d-fb0fba0523a0 · inbound

Benchmarking and Explaining Deep Learning Cortical Lesion MRI Segmentation in Multiple Sclerosis cites this paper.

Benchmarking and Explaining Deep Learning Cortical Lesion MRI Segmentation in Multiple Sclerosis Revisiting MAE pre-training for 3D medical image segmentation

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:00:28.640006Z

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=2026-08-06T17:00:28.352977Z digest=sha256:e0f526974943edcc61f3aabe0b2c1f8e669fd370beb35dcff4bcbbbbae3b8d16