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Paper Citation Record · LEDGER

SegViT: Semantic Segmentation with Plain Vision Transformers

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2210.05844.

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

pith.paper-citation-record.v1
2210.05844 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:13:14.037130Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:27:13.320638Z

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 cf78f1dc-2041-4397-a1bc-6c11ec7ea140 · inbound

LVS-Net: A Lightweight Vessels Segmentation Network for Retinal Image Analysis cites this paper.

LVS-Net: A Lightweight Vessels Segmentation Network for Retinal Image Analysis SegViT: Semantic Segmentation with Plain Vision Transformers

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T20:13:14.037130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:13:14.037130Z digest=sha256:ec9ee701853d1805b33502239b2d6a9527a59a3a4495acd3ec006e86c76f3f7d

Observation 985d6b87-cab2-41ab-ad9d-11b980a49e41 · inbound

AI Meets Maritime Training: Precision Analytics for Enhanced Safety and Performance cites this paper.

AI Meets Maritime Training: Precision Analytics for Enhanced Safety and Performance SegViT: Semantic Segmentation with Plain Vision Transformers

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T20:59:47.577128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:59:47.577128Z digest=sha256:3ee344c3da1b3262d3b66f9df210eddc7a218f5793e6294a9c7f129d72ada8d3

Observation 47a7cf75-ee5e-4032-bffa-08739de83731 · inbound

FastSmoothSAM: A Fast Smooth Method For Segment Anything Model cites this paper.

FastSmoothSAM: A Fast Smooth Method For Segment Anything Model SegViT: Semantic Segmentation with Plain Vision Transformers

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T15:47:41.920866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:47:41.920866Z digest=sha256:c2bfcdc01219879a2e4fd87e830755ee9b2e142e73feeeea3480c625b8e30d28

Observation cfaa2b21-284a-417e-b48b-260b08b427c9 · inbound

Glass Surface Segmentation with an RGB-D Camera via Weighted Feature Fusion for Service Robots cites this paper.

Glass Surface Segmentation with an RGB-D Camera via Weighted Feature Fusion for Service Robots SegViT: Semantic Segmentation with Plain Vision Transformers

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T05:34:47.258884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:34:47.258884Z digest=sha256:e7856c9eb7f6c5a4e4840eebddc1dacfea50f41c0e87aed4f10ad8aaedc6a5ae

Observation dc8391b2-ea6d-4c0d-a773-90763bf627c0 · inbound

Integrating SAM Supervision for 3D Weakly Supervised Point Cloud Segmentation cites this paper.

Integrating SAM Supervision for 3D Weakly Supervised Point Cloud Segmentation SegViT: Semantic Segmentation with Plain Vision Transformers

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:27:13.324585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T15:27:12.813410Z digest=sha256:f21f8c8bff3dc401139c2e47e4b4e43765a0cfee69b04b6236075ebcd90bf05e

Observation f1ea6648-0331-44f4-b927-67b6b67ac29c · inbound

I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation cites this paper.

I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation SegViT: Semantic Segmentation with Plain Vision Transformers

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:09.296886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:09.296886Z digest=sha256:e155fe15330c0c4aa9d51fae5344de505bbbef3d25cb5bf51b458db3d9c6ed4a