Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2304.13973.
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 2026-08-06T23:26:18.581465Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T00:09:14.333398Z
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 c8cf78e4-d47c-4ff0-978f-03ffd31d26dc · inbound
On Efficient Variants of Segment Anything Model: A Survey cites this paper.
On Efficient Variants of Segment Anything Model: A Survey SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model
Reference 64
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T19:43:23.316611Z
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.
Observation 9fa15cab-d076-4581-a003-9a11c80b32aa · inbound
Mobile Image Analysis Application for Mantoux Skin Test cites this paper.
Mobile Image Analysis Application for Mantoux Skin Test SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:26:18.581465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 85fa21a2-595f-47f0-baae-6d12cc2753fb · inbound
Fully Automated SAM for Single-source Domain Generalization in Medical Image Segmentation cites this paper.
Fully Automated SAM for Single-source Domain Generalization in Medical Image Segmentation SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:57:34.930250Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1c61b662-73ef-4d24-abe5-2d30e667316a · inbound
Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis cites this paper.
Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:33:19.253414Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5057741a-0994-4446-9ab5-cbf3a8a06923 · inbound
PEFT-MedSAM: Efficient Fine-Tuning of Medical Foundation Models for Explainable Skin Lesion Segmentation cites this paper.
PEFT-MedSAM: Efficient Fine-Tuning of Medical Foundation Models for Explainable Skin Lesion Segmentation SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model
Reference 55
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T00:09:14.336106Z
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.