Paper Citation Record · LEDGER

Multimodal Whole Slide Foundation Model for Pathology

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2411.19666.

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

pith.paper-citation-record.v1
2411.19666 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:36:44.362947Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T14:04:44.735098Z

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 9c87c09b-b9c3-4f80-af66-011a8a360378 · inbound

From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research cites this paper.

From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research Multimodal Whole Slide Foundation Model for Pathology

Reference 163

Resolution: verified exact; arxiv_id, observed 2026-05-19T05:12:05.132851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 76b49cbd-f726-4b1e-8943-dd22083913f5 · inbound

A Large-Scale Benchmark of Cross-Modal Learning for Histology and Gene Expression in Spatial Transcriptomics cites this paper.

A Large-Scale Benchmark of Cross-Modal Learning for Histology and Gene Expression in Spatial Transcriptomics Multimodal Whole Slide Foundation Model for Pathology

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T05:36:44.362947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df717a34-aec1-43f8-b936-bb031353ddfd · inbound

Enhancing Zero-Shot Brain Tumor Subtype Classification via Fine-Grained Patch-Text Alignment cites this paper.

Enhancing Zero-Shot Brain Tumor Subtype Classification via Fine-Grained Patch-Text Alignment Multimodal Whole Slide Foundation Model for Pathology

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T05:31:17.711555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d32f711-a32a-4423-bcce-0ba9e64fb91a · inbound

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification cites this paper.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Multimodal Whole Slide Foundation Model for Pathology

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.149976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6a7cdf0-383d-4701-bf1f-54e7613314d9 · inbound

Boosting Pathology Foundation Models via Few-shot Prompt-tuning for Rare Cancer Subtyping cites this paper.

Boosting Pathology Foundation Models via Few-shot Prompt-tuning for Rare Cancer Subtyping Multimodal Whole Slide Foundation Model for Pathology

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T17:45:04.707229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fd9821e-5621-494c-8901-a3d25d0558db · inbound

Integrating Pathology and CT Imaging for Personalized Recurrence Risk Prediction in Renal Cancer cites this paper.

Integrating Pathology and CT Imaging for Personalized Recurrence Risk Prediction in Renal Cancer Multimodal Whole Slide Foundation Model for Pathology

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T14:12:17.868715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 928ac482-e845-4a97-9593-09a4c78d1b4e · inbound

PathFLIP: Fine-grained Language-Image Pretraining for Versatile Computational Pathology cites this paper.

PathFLIP: Fine-grained Language-Image Pretraining for Versatile Computational Pathology Multimodal Whole Slide Foundation Model for Pathology

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T15:17:38.056149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b824418-28f8-4b27-8ba2-e0299ec73a41 · inbound

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

MOOZY: A Patient-First Foundation Model for Computational Pathology Multimodal Whole Slide Foundation Model for Pathology

Reference 20

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 b575d5f7-4879-400f-88cc-cef657767185 · inbound

EndoGov: A knowledge-governed multi-agent expert system for endometrial cancer risk stratification cites this paper.

EndoGov: A knowledge-governed multi-agent expert system for endometrial cancer risk stratification Multimodal Whole Slide Foundation Model for Pathology

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:36:14.254732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 27501e9b-40e7-4c71-8a9d-5ed753b04c6b · inbound

ConceptM$^3$oE: Concept-Guided Multimodal Mixture of Experts for Interpretable Computational Pathology cites this paper.

ConceptM$^3$oE: Concept-Guided Multimodal Mixture of Experts for Interpretable Computational Pathology Multimodal Whole Slide Foundation Model for Pathology

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:04:44.737055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1b08cf40-1ccf-4f32-8147-89cd1435f7ca · inbound

Mitigating Batch Effects in Histopathology via Language-Mediated Robust Embedding Generation cites this paper.

Mitigating Batch Effects in Histopathology via Language-Mediated Robust Embedding Generation Multimodal Whole Slide Foundation Model for Pathology

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-30T10:04:36.027340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 76314461-29e7-4c9b-8d4a-f8622272a9b7 · inbound

Value-Monotonicity Matters: A Concordance Loss for Deep Survival Prediction cites this paper.

Value-Monotonicity Matters: A Concordance Loss for Deep Survival Prediction Multimodal Whole Slide Foundation Model for Pathology

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T19:58:25.119327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e02d0bc6-f6e3-4b26-bf96-79817e46c1a5 · inbound

From Multi-Resolution Cells to Gigapixel Whole Slide Images Foundation Model for Computational Pathology cites this paper.

From Multi-Resolution Cells to Gigapixel Whole Slide Images Foundation Model for Computational Pathology Multimodal Whole Slide Foundation Model for Pathology

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T17:47:37.569467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.