Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.14153.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:19:11.221739Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-04T23:14:03.632644Z
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 346b56a2-c4a1-4b56-b126-2f40b1987f2a · inbound
Hierarchical Self-Prompting SAM: A Prompt-Free Medical Image Segmentation Framework cites this paper.
Hierarchical Self-Prompting SAM: A Prompt-Free Medical Image Segmentation Framework De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:19:11.221739Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 99146d75-9310-4b65-b881-44323d1dc1e5 · 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 De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:56:03.792775Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3d959cb5-82d5-4a3d-bac5-d53a136a0d40 · inbound
MambaVesselNet++: A Hybrid CNN-Mamba Architecture for Medical Image Segmentation cites this paper.
MambaVesselNet++: A Hybrid CNN-Mamba Architecture for Medical Image Segmentation De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:55:43.547878Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5bc25384-eda8-4ee3-9bc5-ecbdb4af75ea · inbound
Topology Optimization in Medical Image Segmentation with Fast Euler Characteristic cites this paper.
Topology Optimization in Medical Image Segmentation with Fast Euler Characteristic De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:33:39.645873Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4c678363-1c4c-44be-b9d3-633ee1f2f980 · inbound
Co-Seg: Mutual Prompt-Guided Collaborative Learning for Tissue and Nuclei Segmentation cites this paper.
Co-Seg: Mutual Prompt-Guided Collaborative Learning for Tissue and Nuclei Segmentation De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
Reference 33
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-04T23:14:03.808612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.