Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2011.06252.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T05:35:22.157872Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T04:41:00.275442Z
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 b9bebc0f-c1fd-4e21-8c0a-f6792156b8af · inbound
SVGS-DSGAT: An IoT-Enabled Innovation in Underwater Robotic Object Detection Technology cites this paper.
SVGS-DSGAT: An IoT-Enabled Innovation in Underwater Robotic Object Detection Technology SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:29:45.844115Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f792d9d2-8589-45d7-b79e-9e2eb6e7a605 · inbound
Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement cites this paper.
Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T05:35:22.157872Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0dfdbab7-afdf-4a45-b8b9-5c80e7cb50e7 · inbound
UniV2D: Bridging Visual Restoration and Semantic Perception for Underwater Salient Object Detection cites this paper.
UniV2D: Bridging Visual Restoration and Semantic Perception for Underwater Salient Object Detection SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T04:41:00.284172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.