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Paper Citation Record · LEDGER

A Recent Survey of Vision Transformers for Medical Image Segmentation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.00634.

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

pith.paper-citation-record.v1
2312.00634 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:07:20.368225Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:55:44.244094Z

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 a2c8ee59-46e2-4059-aa34-080ac3a37cb1 · inbound

AutoGen Driven Multi Agent Framework for Iterative Crime Data Analysis and Prediction cites this paper.

AutoGen Driven Multi Agent Framework for Iterative Crime Data Analysis and Prediction A Recent Survey of Vision Transformers for Medical Image Segmentation

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.368225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.368225Z digest=sha256:9dd8d8f13bd6822dfdd8920de9b254c94edce6af2b1e6daae5afdbb3a6b426b2

Observation afcd0927-6076-4aa1-b263-c260bd91e7ef · inbound

Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention cites this paper.

Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention A Recent Survey of Vision Transformers for Medical Image Segmentation

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:55:44.249219Z

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=2026-08-06T23:55:43.662674Z digest=sha256:c8b3b1e377ad8cbad6b3a27ebae7fbb7105e6fd541d8f32588b0234d6c77dade