Paper Citation Record · LEDGER

Fully Transformer Networks for Semantic Image Segmentation

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2106.04108.

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

pith.paper-citation-record.v1
2106.04108 v3

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 2026-08-16T06:30:59.297886+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:10:54.049533Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T01:12:54.872795Z

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 a3e2cc5b-8e8c-4d04-979f-fe1da9ce14b4 · inbound

Image Segmentation with transformers: An Overview, Challenges and Future cites this paper.

Image Segmentation with transformers: An Overview, Challenges and Future Fully Transformer Networks for Semantic Image Segmentation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.049533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9127ecf-4e20-4263-a5a7-206fe8be6e9c · inbound

Deeply Dual Supervised learning for melanoma recognition cites this paper.

Deeply Dual Supervised learning for melanoma recognition Fully Transformer Networks for Semantic Image Segmentation

Reference 110

Resolution: verified exact; arxiv_id, observed 2026-05-19T01:12:54.876486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c066f40a-e2a0-475b-a9af-78736b8f9e3c · inbound

Edge Detection for Organ Boundaries via Top Down Refinement and SubPixel Upsampling cites this paper.

Edge Detection for Organ Boundaries via Top Down Refinement and SubPixel Upsampling Fully Transformer Networks for Semantic Image Segmentation

Reference 103

Resolution: verified exact; arxiv_id, observed 2026-05-19T00:46:56.022756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0b11e308-f4bc-4f20-913a-d661468c6604 · inbound

DualResolution Residual Architecture with Artifact Suppression for Melanocytic Lesion Segmentation cites this paper.

DualResolution Residual Architecture with Artifact Suppression for Melanocytic Lesion Segmentation Fully Transformer Networks for Semantic Image Segmentation

Reference 106

Resolution: verified exact; arxiv_id, observed 2026-05-19T00:42:54.446679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f90df2f7-1a29-4bda-8235-9c4dd191f635 · inbound

VesselRW: Weakly Supervised Subcutaneous Vessel Segmentation via Learned Random Walk Propagation cites this paper.

VesselRW: Weakly Supervised Subcutaneous Vessel Segmentation via Learned Random Walk Propagation Fully Transformer Networks for Semantic Image Segmentation

Reference 102

Resolution: verified exact; arxiv_id, observed 2026-05-19T00:41:56.249777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.