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Paper Citation Record · LEDGER

SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.00035.

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

pith.paper-citation-record.v1
2305.00035 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:32:29.079362Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T04:13:53.147257Z

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 9585f912-a7ef-47ab-b4a6-f32fb1ffc70e · inbound

Data-Centric Foundation Models in Computational Healthcare: A Survey cites this paper.

Data-Centric Foundation Models in Computational Healthcare: A Survey SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-24T04:13:53.150046Z

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.

source=pdf_text observed=2026-05-24T04:13:05.328492Z digest=sha256:67a698cfa0fc9b2ce27cb4d530de2f66583a0d3e026ef1b705799c9478366b5e

Observation 78e294a2-90df-4742-94a8-21eb9b8436c2 · inbound

Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery cites this paper.

Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T10:32:29.079362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:32:29.079362Z digest=sha256:a6a4ffeacde1e0e41b8dad3ed186fa725b1b8e4acdd6ddbdc0c59b41591ef74b

Observation 6299ff58-eb2a-45ff-bafd-621fcc6277b4 · inbound

Prompt Mechanisms in Medical Imaging: A Comprehensive Survey cites this paper.

Prompt Mechanisms in Medical Imaging: A Comprehensive Survey SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T22:02:24.786642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:02:24.786642Z digest=sha256:1496c3ba519323eaac4e410a7497cc436902a3468bfa07267141229d78425359

Observation 852da6fe-ff25-4316-bcec-362598332ea9 · inbound

Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery cites this paper.

Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:56:11.060194Z

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.

source=pdf_text observed=2026-05-10T05:54:47.183674Z digest=sha256:09f5ff626ab500c0a7585a06bb01ed1ec0711054fa1a446e0f4bcf84439b73a3

Observation a9ba287a-0670-4715-8da9-2a607d498556 · inbound

Learning from Noisy Prompts: Saliency-Guided Prompt Distillation for Robust Segmentation with SAM cites this paper.

Learning from Noisy Prompts: Saliency-Guided Prompt Distillation for Robust Segmentation with SAM SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:31:14.725395Z

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.

source=pdf_text observed=2026-05-08T08:37:19.723297Z digest=sha256:69408d9ee2538c643038458c8d056609bc6021807a7031c84c6a0874d4464eac