Paper Citation Record · LEDGER

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification

As of 23 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2607.08162.

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

pith.paper-citation-record.v1
2607.08162 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T12:05:14.211414Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

17 of 17 outbound references displayed

verified exact1
verified fuzzy16
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 156194a2-a441-4919-a852-9151693966df · outbound

This paper cites A whole-slide foundation model for digital pathology from real-world data,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification A whole-slide foundation model for digital pathology from real-world data,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.809459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d97c1078-4e60-4394-99b3-d8bbd48a0222 · outbound

This paper cites Clinical-grade computational pathology using weakly supervised deep learning on whole slide images,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Clinical-grade computational pathology using weakly supervised deep learning on whole slide images,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.805812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c4be43b0-2806-4c55-ad0b-3878f6acc5c6 · outbound

This paper cites Data-efficient and weakly supervised computational pathology on whole-slide images,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Data-efficient and weakly supervised computational pathology on whole-slide images,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.803782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 542454a5-aeb1-44e8-a74b-fb282022f0fb · outbound

This paper cites Artificial intelligence for diagnosis and gleason grading of prostate cancer: the panda challenge,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Artificial intelligence for diagnosis and gleason grading of prostate cancer: the panda challenge,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.802236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9e9dadbe-bf3b-4d95-b79d-7cfbb47e41e0 · outbound

This paper cites A clinical bench- mark of public self-supervised pathology foundation models,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification A clinical bench- mark of public self-supervised pathology foundation models,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.807551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bc3fec74-bb73-4636-940b-ef5b69081d9f · outbound

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

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-10T12:07:03.451007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d4939a72-1016-40f0-bc97-106108c5695f · outbound

This paper cites Masked au- toencoders are scalable vision learners.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Masked au- toencoders are scalable vision learners

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.800595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f350ea7f-60b9-40dc-89eb-0e22acb6617e · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification An image is worth 16x16 words: Transformers for image recognition at scale

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.797940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b843c86b-72f2-4fcc-9bbf-d1eb9081efcd · outbound

This paper cites Mitosis domain generalization in histopathol- ogy images – the midog challenge,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Mitosis domain generalization in histopathol- ogy images – the midog challenge,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.816484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation dac11db0-583e-4003-b46b-6aa8af14154f · outbound

This paper cites Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.795339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 38363332-5d86-4728-aea8-354ccb131d8e · outbound

This paper cites From detection of individual metastases to classification of lymph node status at the patient level: the camelyon17 challenge,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification From detection of individual metastases to classification of lymph node status at the patient level: the camelyon17 challenge,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.810964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f12fc7c9-e732-49b0-8ffc-8d1cfcd89c83 · outbound

This paper cites Bracs: A dataset for breast carcinoma subtyping in h&e histology images,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Bracs: A dataset for breast carcinoma subtyping in h&e histology images,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.793769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 07a9ef78-8dd1-4d67-9e36-da1b1229c0f1 · outbound

This paper cites Lomae: Simple streamlined low-level masked autoencoders for robust, generalized, and interpretable low-dose ct denoising,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Lomae: Simple streamlined low-level masked autoencoders for robust, generalized, and interpretable low-dose ct denoising,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.813073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6db8a717-ac21-4dc6-b16a-058895397a60 · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification A simple framework for contrastive learning of visual representations,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.791412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a28ec854-035d-4033-81c7-57d1d21f6812 · outbound

This paper cites Self supervised contrastive learning for digital histopathology,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Self supervised contrastive learning for digital histopathology,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.814549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a7a502f9-d152-4196-9ac8-b97628a8d250 · outbound

This paper cites Weighted kappa: Nominal scale agreement with provision for scaled disagreement or partial credit,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Weighted kappa: Nominal scale agreement with provision for scaled disagreement or partial credit,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.820060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 62b1280a-69e5-4d05-99dc-b186b46e87a8 · outbound

This paper cites Confidence interval for micro-averaged f1 and macro-averaged f1 scores,.

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification Confidence interval for micro-averaged f1 and macro-averaged f1 scores,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:07:03.817952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.