Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentation
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2308.08746.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:54:38.058935Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T17:56:04.107820Z
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 9e8948c0-1723-4daf-a779-d95226e47cee · inbound
Surg-SegFormer: A Dual Transformer-Based Model for Holistic Surgical Scene Segmentation cites this paper.
Surg-SegFormer: A Dual Transformer-Based Model for Holistic Surgical Scene Segmentation SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentation
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:53:27.554513Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 47166685-3f7f-4e81-b84a-36d59a0de644 · inbound
CLIP-RL: Surgical Scene Segmentation Using Contrastive Language-Vision Pretraining & Reinforcement Learning cites this paper.
CLIP-RL: Surgical Scene Segmentation Using Contrastive Language-Vision Pretraining & Reinforcement Learning SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentation
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:54:38.058935Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24b2c8de-2640-4836-b7e8-210d704f6dc6 · 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 SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentation
Reference 74
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T17:56:04.111852Z
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.