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Paper Citation Record · LEDGER

RevSAM2: Prompt SAM2 for Medical Image Segmentation via Reverse-Propagation without Fine-tuning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.04298.

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

pith.paper-citation-record.v1
2409.04298 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:32:46.799855Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T16:13:53.755205Z

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 6a0871a8-7091-4d27-a9f2-de32ee68e9f0 · inbound

Exploring Few-Shot Defect Segmentation in General Industrial Scenarios with Metric Learning and Vision Foundation Models cites this paper.

Exploring Few-Shot Defect Segmentation in General Industrial Scenarios with Metric Learning and Vision Foundation Models RevSAM2: Prompt SAM2 for Medical Image Segmentation via Reverse-Propagation without Fine-tuning

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-09T16:13:53.763932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T16:13:53.265324Z digest=sha256:300cde3723b046f13ada890795a4dd963f3c39686c9a926d2a1779974a88493b

Observation f429e344-cfab-405f-a769-313056c3c5d9 · inbound

SAM2-SGP: Enhancing SAM2 for Medical Image Segmentation via Support-Set Guided Prompting cites this paper.

SAM2-SGP: Enhancing SAM2 for Medical Image Segmentation via Support-Set Guided Prompting RevSAM2: Prompt SAM2 for Medical Image Segmentation via Reverse-Propagation without Fine-tuning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-15T18:32:46.799855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:32:46.799855Z digest=sha256:1601bf7ac57c22156ca4629b446e023ecede682ecc9a1cc4babd12e186d92639

Observation 44822c76-05af-4298-9e4f-0c32ad0101c4 · inbound

SAMRI-3D: Adapting SAM2 for 3D MRI Segmentation with Global Volume Tokens cites this paper.

SAMRI-3D: Adapting SAM2 for 3D MRI Segmentation with Global Volume Tokens RevSAM2: Prompt SAM2 for Medical Image Segmentation via Reverse-Propagation without Fine-tuning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-01T16:27:27.832070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T16:27:27.832070Z digest=sha256:7d65b2bb78bf108314f8444bbd0382979d8a5b60d917dd114b7efdf772dbfdf6