Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2404.10156.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:26:56.797903Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T05:30:23.456663Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
0
pith, observed 2026-08-10T05:30:23.456663Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 181d61da-184e-4c65-a3f1-fee1fa5edb7f · inbound
DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling cites this paper.
DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T10:26:56.993060Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.