Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
RadSAM: Segmenting 3D radiological images with a 2D promptable model
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2504.20837.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:08:26.408071Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T16:29:57.802183Z
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 d1ff5acf-4b03-4102-b5c0-21a51957fe45 · inbound
CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering cites this paper.
CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering RadSAM: Segmenting 3D radiological images with a 2D promptable model
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:08:26.408071Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e9171a09-33fc-46a5-93db-8f27f8b10ba9 · inbound
RAPS-3D: Efficient interactive segmentation for 3D radiological imaging cites this paper.
RAPS-3D: Efficient interactive segmentation for 3D radiological imaging RadSAM: Segmenting 3D radiological images with a 2D promptable model
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:38:39.918277Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c01b190-cb49-46b2-90e9-86c847f28d91 · inbound
Jolia: Concept-Level Vision-Language Alignment for 3D CT Contrastive Learning cites this paper.
Jolia: Concept-Level Vision-Language Alignment for 3D CT Contrastive Learning RadSAM: Segmenting 3D radiological images with a 2D promptable model
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T16:29:57.803714Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.