Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Segment anything model 2: an application to 2D and 3D medical images
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2408.00756.
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 2026-08-07T11:52:39.281260Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T03:47:35.355849Z
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 abbb45df-6af8-47da-88fa-5ea6e115d231 · inbound
On Efficient Variants of Segment Anything Model: A Survey cites this paper.
On Efficient Variants of Segment Anything Model: A Survey Segment anything model 2: an application to 2D and 3D medical images
Reference 93
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T19:43:23.165341Z
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 35c29cac-6a12-481e-84a0-ac4ac2ca8add · inbound
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost cites this paper.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment anything model 2: an application to 2D and 3D medical images
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:39.281260Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8616e1d2-24f2-4159-9007-2ccb1cf02628 · inbound
Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration? cites this paper.
Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration? Segment anything model 2: an application to 2D and 3D medical images
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:27:03.524086Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 570051bd-ff7c-4f3e-90fc-895cd0a5a2ac · inbound
Comparing SAM 2 and SAM 3 for Zero-Shot Segmentation of 3D Medical Data cites this paper.
Comparing SAM 2 and SAM 3 for Zero-Shot Segmentation of 3D Medical Data Segment anything model 2: an application to 2D and 3D medical images
Reference 6
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T04:39:02.649648Z
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 9f805132-1b09-4880-a664-444ac2013ac0 · inbound
Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation cites this paper.
Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation Segment anything model 2: an application to 2D and 3D medical images
Reference 43
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T06:56:44.577877Z
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 7da7edd6-4d1a-4016-bfa3-92805f411ba2 · inbound
Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation cites this paper.
Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation Segment anything model 2: an application to 2D and 3D medical images
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:27:07.697655Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84194445-714c-4fb4-8bb8-f26a955bf27c · inbound
FMplex: Model Virtualization for Serving Extensible Foundation Models cites this paper.
FMplex: Model Virtualization for Serving Extensible Foundation Models Segment anything model 2: an application to 2D and 3D medical images
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T03:47:35.357323Z
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.