Pith. sign in

Paper Citation Record · LEDGER

ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2207.14552.

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

pith.paper-citation-record.v1
2207.14552 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:25:17.480628Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T06:45:29.655913Z

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 5cbe8df8-be18-4fe4-8c7d-40270165a402 · inbound

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation cites this paper.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T12:25:17.480628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:25:17.480628Z digest=sha256:fbc48a83a144d7e3b8d8aa525a67ab78dcc6ac4338e61134dc396b485920c313

Observation 45b5c2b3-a1b0-46e4-8965-5b5e6f537452 · inbound

A Large-Scale Referring Remote Sensing Image Segmentation Dataset and Benchmark cites this paper.

A Large-Scale Referring Remote Sensing Image Segmentation Dataset and Benchmark ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T11:01:49.237433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:01:49.237433Z digest=sha256:acb1b0ed3dd49109806a1481d7810109a439394f4bbd485e71bb28718e79e7b0

Observation 2079cf61-03b4-4c2c-ae85-9e77a21c7051 · inbound

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms cites this paper.

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation

Reference 97

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:14:19.444966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T06:09:54.742202Z digest=sha256:5d3334996794be7646f89de809f57bf4f6dc0213709ce11eb716c8f48946d3b8

Observation 781e2eb8-b716-4f2d-82cf-f75e87311d3b · inbound

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms cites this paper.

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation

Reference 92

Resolution
verified exact
arxiv_id, observed 2026-07-01T06:45:29.657859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-01T06:38:06.306930Z digest=sha256:6ea111404d02d84896a0ae8667446014875e6fed3220e236e9a208985a300e6c

Observation caa7d1ac-c632-42be-b4df-537242085a9b · inbound

A Large-Scale Dataset and a New Method for RemoteSensing Traffic Object Segmentation cites this paper.

A Large-Scale Dataset and a New Method for RemoteSensing Traffic Object Segmentation ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-11T22:49:41.476167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T22:49:41.476167Z digest=sha256:846080bf1e62334cf245cf89f9f809c02808882baebc533914f39859ebe43ec0