Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
UVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation via Segment Anything Model
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.12659.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T05:23:20.266079Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T08:23:15.699434Z
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 448178a3-7709-43d4-bf26-f169c0e191c6 · inbound
On Efficient Variants of Segment Anything Model: A Survey cites this paper.
On Efficient Variants of Segment Anything Model: A Survey UVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation via Segment Anything Model
Reference 85
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T19:43:23.105209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation f781c3d2-c427-4d55-9b9d-3fe9f2feb0d0 · inbound
ZISVFM: Zero-Shot Object Instance Segmentation in Indoor Robotic Environments with Vision Foundation Models cites this paper.
ZISVFM: Zero-Shot Object Instance Segmentation in Indoor Robotic Environments with Vision Foundation Models UVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation via Segment Anything Model
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T05:23:20.266079Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed16d65f-c386-48c6-833d-fad050a891f9 · inbound
GMOS: Grounding Moving Object Segmentation in 3D Space and Time cites this paper.
GMOS: Grounding Moving Object Segmentation in 3D Space and Time UVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation via Segment Anything Model
Reference 87
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T08:23:15.700909Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.