Paper Citation Record · LEDGER

WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2204.06455.

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

pith.paper-citation-record.v1
2204.06455 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:21:46.495694Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T19:33:54.355380Z

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 70efd34c-a403-4d2d-871f-1df320e7d23c · inbound

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology cites this paper.

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T14:21:46.495694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad73bf62-d4c7-4cc2-b77f-abafaa5c729c · inbound

HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency Regularization cites this paper.

HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency Regularization WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:26.445867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7537e34d-8a61-41c2-bf46-7578218f415a · inbound

Superpixel Boundary Correction for Weakly-Supervised Semantic Segmentation on Histopathology Images cites this paper.

Superpixel Boundary Correction for Weakly-Supervised Semantic Segmentation on Histopathology Images WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T21:49:18.238925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 333e4e97-f182-4d6d-a115-01d06a3756e9 · inbound

Segment Anything in Pathology Images with Natural Language cites this paper.

Segment Anything in Pathology Images with Natural Language WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-06T22:42:11.960256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66adc0b8-56bc-46dd-be32-9c78c8c5948b · inbound

A tissue and cell-level annotated H&E and PD-L1 histopathology image dataset in non-small cell lung cancer cites this paper.

A tissue and cell-level annotated H&E and PD-L1 histopathology image dataset in non-small cell lung cancer WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T15:33:32.060104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56069b37-72b4-4a67-bed2-cddbfb70fcfb · inbound

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model cites this paper.

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T14:55:44.782568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 408dae5d-efe9-478c-bb56-a0da6446fa87 · inbound

A Clinically Validated Foundation Model for Comprehensive Lung Pathology Interpretation cites this paper.

A Clinically Validated Foundation Model for Comprehensive Lung Pathology Interpretation WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:33:54.356763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4183fdb5-bd9b-4781-9650-acc7fee831ce · inbound

A Clinically Validated Foundation Model for Comprehensive Lung Pathology Interpretation cites this paper.

A Clinically Validated Foundation Model for Comprehensive Lung Pathology Interpretation WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-02T13:12:52.921604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41e332f6-f600-40f5-8366-18a8af726a7a · inbound

ALICE: Learning a General-Purpose Pathology Foundation Model from Vision, Vision-Language, and Slide-Level Experts cites this paper.

ALICE: Learning a General-Purpose Pathology Foundation Model from Vision, Vision-Language, and Slide-Level Experts WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 66

Resolution: unresolved; no resolver link, observed 2026-07-13T02:23:52.225787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0f5f5f1-7a47-4ac5-923a-a164acf8687c · 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 WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T17:47:38.361028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.