Paper Citation Record · LEDGER

A Comprehensive Survey on Segment Anything Model for Vision and Beyond

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2305.08196.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2305.08196 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:56:35.805048Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-23T19:43:23.554334Z

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 46958f99-f6f6-4893-9537-d27ca41f2b8b · inbound

On Efficient Variants of Segment Anything Model: A Survey cites this paper.

On Efficient Variants of Segment Anything Model: A Survey A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:43:23.561650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 171d2d81-0c12-45d9-bd94-4dc17e32486e · inbound

Diffusion-empowered AutoPrompt MedSAM cites this paper.

Diffusion-empowered AutoPrompt MedSAM A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T10:56:35.805048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ce87ea9-bc25-4025-ac36-6cede8e8d2be · inbound

Local Differential Privacy is Not Enough: A Sample Reconstruction Attack against Federated Learning with Local Differential Privacy cites this paper.

Local Differential Privacy is Not Enough: A Sample Reconstruction Attack against Federated Learning with Local Differential Privacy A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T10:19:52.644129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c4ee73d-5102-4752-ba2e-58d8b1209621 · inbound

Prompt Engineering in Segment Anything Model: Methodologies, Applications, and Emerging Challenges cites this paper.

Prompt Engineering in Segment Anything Model: Methodologies, Applications, and Emerging Challenges A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-06T17:56:03.824585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa84629d-9b14-4539-8a40-97dde4d0b632 · 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 A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T14:57:34.866983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75071e73-10a1-4455-a3bc-642fb27a86a5 · inbound

MergeSAM: Unsupervised change detection of remote sensing images based on the Segment Anything Model cites this paper.

MergeSAM: Unsupervised change detection of remote sensing images based on the Segment Anything Model A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T11:27:58.734230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07060d5a-f3ab-4c2b-a602-5ea3afc3127b · inbound

DOMR: Establishing Cross-View Segmentation via Dense Object Matching cites this paper.

DOMR: Establishing Cross-View Segmentation via Dense Object Matching A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T01:01:25.087870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9340981a-21eb-493a-8e2e-235ee97c4143 · inbound

Grouped Speculative Decoding for Autoregressive Image Generation cites this paper.

Grouped Speculative Decoding for Autoregressive Image Generation A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-05T21:57:10.611602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 975d18c5-c78c-4e7b-ba3d-8c7e2403d97d · inbound

Automated Annotation of Shearographic Measurements Enabling Weakly Supervised Defect Detection cites this paper.

Automated Annotation of Shearographic Measurements Enabling Weakly Supervised Defect Detection A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T00:21:23.702373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 65537be1-04a5-424a-9774-1455b5868f96 · inbound

SegMoTE: Token-Level Mixture of Experts for Medical Image Segmentation cites this paper.

SegMoTE: Token-Level Mixture of Experts for Medical Image Segmentation A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-02T21:47:28.584556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5803a359-1899-43ae-8d41-34b2680eec01 · inbound

ZMIS-SAM: Segment Anything Model Enhanced with Wavelet Transform for Zooplankton Microscopy Image Instance Segmentation cites this paper.

ZMIS-SAM: Segment Anything Model Enhanced with Wavelet Transform for Zooplankton Microscopy Image Instance Segmentation A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-01T05:13:24.443510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.