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Paper Citation Record · LEDGER

UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2402.16663.

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

pith.paper-citation-record.v1
2402.16663 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:05:58.489518Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T13:55:43.908561Z

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 4410f24f-c9b9-4bee-b210-13c3c650e8e2 · inbound

CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation cites this paper.

CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T19:59:54.535144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:59:54.535144Z digest=sha256:ca6d10650c670a5655f41338bdbe734dc53469ab9e05808d5f14c5a0492102c9

Observation ab0688d8-7df6-42a6-a8a2-4c1a94178a44 · inbound

CellSeg1: Robust Cell Segmentation with One Training Image cites this paper.

CellSeg1: Robust Cell Segmentation with One Training Image UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T04:28:34.535038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:28:34.535038Z digest=sha256:368e5b2b97ad85f0931b5d6517cd709c60383a98a57d6b2a4b1267ec96076124

Observation 5bae21d2-5daa-4787-804f-e904913d84a7 · inbound

Long-tailed Medical Diagnosis with Relation-aware Representation Learning and Iterative Classifier Calibration cites this paper.

Long-tailed Medical Diagnosis with Relation-aware Representation Learning and Iterative Classifier Calibration UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-09T05:28:43.583581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T05:28:43.583581Z digest=sha256:aa437605b2596ff1b0cc22bbacea7bd9d529da522a692a5fde5e374e163f400d

Observation 6d60d024-f5c4-48ec-9393-bd941af9102c · inbound

SAM4EM: Efficient memory-based two stage prompt-free segment anything model adapter for complex 3D neuroscience electron microscopy stacks cites this paper.

SAM4EM: Efficient memory-based two stage prompt-free segment anything model adapter for complex 3D neuroscience electron microscopy stacks UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T05:05:58.489518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:05:58.489518Z digest=sha256:5da3e1437df717fbbe56648d807f565216ad262a8717c2935ef79b0deeb7f378

Observation f21e6825-c589-4b10-8883-f4eb16a92d3e · inbound

Rethinking Decoder Design: Improving Biomarker Segmentation Using Depth-to-Space Restoration and Residual Linear Attention cites this paper.

Rethinking Decoder Design: Improving Biomarker Segmentation Using Depth-to-Space Restoration and Residual Linear Attention UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T18:54:17.953794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:54:17.953794Z digest=sha256:a973c681bf14113ab48f7e27a7d205f35a428843dd32fdf334a3cf11b06a4f76

Observation 1abebed7-b100-40b9-b8c0-5d6b94bbecf9 · inbound

CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation cites this paper.

CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T21:53:31.691775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:53:31.691775Z digest=sha256:d642f554607d09b24a7c1ae290480c83d8b80838d8017974499b564fc505c559

Observation bb207806-6c93-459e-aa54-b78fdaa45c55 · inbound

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

Prompt Mechanisms in Medical Imaging: A Comprehensive Survey UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T22:02:24.775532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:02:24.775532Z digest=sha256:8934552611c4739245e8b329284629ee7333fbc7969ef88c8863d72f108b0201

Observation 6638895e-50aa-40ca-9caf-b601790a357d · inbound

MambaVesselNet++: A Hybrid CNN-Mamba Architecture for Medical Image Segmentation cites this paper.

MambaVesselNet++: A Hybrid CNN-Mamba Architecture for Medical Image Segmentation UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-06T13:55:43.912230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T13:55:41.737366Z digest=sha256:4cbd50c46c0c54001d5d87356696dcf5c0eb830abe5cdf7ff796d486db69dc3d