Paper Citation Record · LEDGER

Training state-of-the-art pathology foundation models with orders of magnitude less data

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2504.05186.

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

pith.paper-citation-record.v1
2504.05186 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:31:20.476331Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T22:52:45.181509Z

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 54b60432-9195-4c1f-8a5b-2e3c45aaf800 · inbound

MOOZY: A Patient-First Foundation Model for Computational Pathology cites this paper.

MOOZY: A Patient-First Foundation Model for Computational Pathology Training state-of-the-art pathology foundation models with orders of magnitude less data

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-13T17:15:51.142086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56ca0f38-26b6-493e-8e52-5bb9b0e73fe8 · inbound

PC-MIL: Decoupling Feature Resolution from Supervision Scale in Whole-Slide Learning cites this paper.

PC-MIL: Decoupling Feature Resolution from Supervision Scale in Whole-Slide Learning Training state-of-the-art pathology foundation models with orders of magnitude less data

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T10:36:02.643180Z

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.

Observation 913345e8-4162-43c5-bde1-c21b6322b44f · inbound

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction cites this paper.

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction Training state-of-the-art pathology foundation models with orders of magnitude less data

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:36:24.413132Z

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.

Observation f4c2dfe5-8d4d-4597-aefa-89e51c06638d · inbound

When Are Multimodal Predictions Biologically Supported? A Diagnostic Evaluation Framework cites this paper.

When Are Multimodal Predictions Biologically Supported? A Diagnostic Evaluation Framework Training state-of-the-art pathology foundation models with orders of magnitude less data

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.183052Z

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.

Observation c28583b6-c084-4d50-b9c1-1fee2e9414ba · inbound

Robustifying pathology foundation models via fine-tuning cites this paper.

Robustifying pathology foundation models via fine-tuning Training state-of-the-art pathology foundation models with orders of magnitude less data

Reference 31

Resolution: malformed identifier; no resolver link, observed 2026-08-15T15:31:20.476331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 744c3c9c-e6f3-44d1-bdaa-2a5f6652b56e · inbound

A Distributional Robustness Margin For Pathology Foundation Models cites this paper.

A Distributional Robustness Margin For Pathology Foundation Models Training state-of-the-art pathology foundation models with orders of magnitude less data

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T02:19:58.284159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.