Paper Citation Record · LEDGER

A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2203.00131.

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

pith.paper-citation-record.v1
2203.00131 v5

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 2026-08-21T06:32:19.484+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:44:03.454893Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

65
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation eaabe570-4afc-496f-8306-2128232b9987 · inbound

Data-Centric Foundation Models in Computational Healthcare: A Survey cites this paper.

Data-Centric Foundation Models in Computational Healthcare: A Survey A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 90

Resolution: verified exact; arxiv_id, observed 2026-05-24T04:13:53.060925Z

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 d957342f-55de-4fba-be69-b65fc9ec2b88 · inbound

FAN-Unet: Enhancing Unet with vision Fourier Analysis Block for Biomedical Image Segmentation cites this paper.

FAN-Unet: Enhancing Unet with vision Fourier Analysis Block for Biomedical Image Segmentation A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T10:44:03.454893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c76e8a0f-fd21-45ec-a155-7fb8f800022d · inbound

MTVNet: Mapping using Transformers for Volumes -- Network for Super-Resolution with Long-Range Interactions cites this paper.

MTVNet: Mapping using Transformers for Volumes -- Network for Super-Resolution with Long-Range Interactions A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T22:30:25.634747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f68e0337-9e8a-4069-a292-243e968f3961 · inbound

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder cites this paper.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 1845

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:53.815699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd4bb7af-5777-4779-ba9d-a3b936ac2855 · inbound

{S$^3$-Mamba}: Small-Size-Sensitive Mamba for Lesion Segmentation cites this paper.

{S$^3$-Mamba}: Small-Size-Sensitive Mamba for Lesion Segmentation A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T12:13:43.218283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70718247-bd02-47f7-b20d-a4283df07e32 · inbound

VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation cites this paper.

VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T10:41:28.467924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e7f76b5-cc8f-4518-b7ed-4ab2f8bc89aa · inbound

Diffusion-empowered AutoPrompt MedSAM cites this paper.

Diffusion-empowered AutoPrompt MedSAM A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-09T10:56:36.007532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d674fce-1018-4224-b1f3-f4ccbf0c3bff · inbound

Learning Segmentation from Radiology Reports cites this paper.

Learning Segmentation from Radiology Reports A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T19:30:53.884007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a78a213-8149-4f24-ae0d-9c80956b44b5 · inbound

Unified Start, Personalized End: Progressive Pruning for Efficient 3D Medical Image Segmentation cites this paper.

Unified Start, Personalized End: Progressive Pruning for Efficient 3D Medical Image Segmentation A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T19:27:19.403665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb9edb25-5fa1-4f3b-b4d5-d8552955443b · inbound

DSVM-UNet : Enhancing VM-UNet with Dual Self-distillation for Medical Image Segmentation cites this paper.

DSVM-UNet : Enhancing VM-UNet with Dual Self-distillation for Medical Image Segmentation A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T10:50:51.457597Z

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 7ed7a175-ce98-43a8-b091-89cc5735b571 · inbound

CDSA-Net:Collaborative Decoupling of Vascular Structure and Background for High-Fidelity Coronary Digital Subtraction Angiography cites this paper.

CDSA-Net:Collaborative Decoupling of Vascular Structure and Background for High-Fidelity Coronary Digital Subtraction Angiography A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T07:26:59.207970Z

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 c0e871c0-8ac6-49e4-bfc8-89620c531ff5 · inbound

MambaLiteUNet: Cross-Gated Adaptive Feature Fusion for Robust Skin Lesion Segmentation cites this paper.

MambaLiteUNet: Cross-Gated Adaptive Feature Fusion for Robust Skin Lesion Segmentation A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-10T00:24:46.684793Z

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 cd1ff12b-838f-4b9c-91fa-deec44dc932a · inbound

GLeVE: Graph-Guided Lesion Grounding with Proposal Verification in 3D CT cites this paper.

GLeVE: Graph-Guided Lesion Grounding with Proposal Verification in 3D CT A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:44:42.095991Z

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.