Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2309.16108.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T18:28:47.206021Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T14:51:42.814105Z
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 f3c30f5f-6149-4898-bfc4-b0c156b7a00d · inbound
Fast Vision Mamba: Pooling Spatial Dimensions for Accelerated Processing cites this paper.
Fast Vision Mamba: Pooling Spatial Dimensions for Accelerated Processing Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T18:28:47.206021Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2b701df4-dc16-463a-9a24-fd2802db01a6 · inbound
LatticeVision: Image to Image Networks for Modeling Non-Stationary Spatial Data cites this paper.
LatticeVision: Image to Image Networks for Modeling Non-Stationary Spatial Data Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T14:51:42.817144Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 7a1cf1dd-2e16-47f7-baed-94aa1499dbac · inbound
A Foundation Model for Spatial Proteomics cites this paper.
A Foundation Model for Spatial Proteomics Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:11:20.028195Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fb0b1aec-6e16-4de8-acec-7229d60d4ad6 · inbound
Using Deep Learning Models Pretrained by Self-Supervised Learning for Protein Localization cites this paper.
Using Deep Learning Models Pretrained by Self-Supervised Learning for Protein Localization Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:36:02.330867Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation fbb9ca86-2383-4d2f-8546-01b0a7f39086 · inbound
LESSViT: Robust Hyperspectral Representation Learning under Spectral Configuration Shift cites this paper.
LESSViT: Robust Hyperspectral Representation Learning under Spectral Configuration Shift Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
Reference 1
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T11:18:13.726145Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.