Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2304.05750.
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 2026-08-16T12:13:07.538168Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T19:32:34.681536Z
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 fe5fd037-9d82-4bf6-a7be-1d0933627059 · inbound
SAFIRE: Segment Any Forged Image Region cites this paper.
SAFIRE: Segment Any Forged Image Region Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T18:11:07.063370Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5e391002-52e0-4b12-853d-8c326f014d0d · inbound
INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation cites this paper.
INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T22:41:21.131935Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8cd4195f-5a2c-4610-9871-4d4789d1547c · inbound
Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation cites this paper.
Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T18:20:58.646301Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 440f525a-bf54-466d-87ca-f42a8862a7d4 · inbound
Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription cites this paper.
Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Reference 83
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T11:34:08.941691Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eec95f6c-b271-43b5-b8e1-72976d3dce7b · inbound
Putting the Segment Anything Model to the Test with 3D Knee MRI - A Comparison with State-of-the-Art Performance cites this paper.
Putting the Segment Anything Model to the Test with 3D Knee MRI - A Comparison with State-of-the-Art Performance Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T12:13:07.538168Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f3668f6a-a9d5-4170-aa87-1d2130cf4688 · inbound
TextureSAM: Towards a Texture Aware Foundation Model for Segmentation cites this paper.
TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:02:53.203778Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c74a54b4-1e69-422c-9bcf-7a50c33598fc · inbound
Segment Concealed Objects with Incomplete Supervision cites this paper.
Segment Concealed Objects with Incomplete Supervision Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:03:57.950180Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 445a282f-9f78-41b1-97ec-6289078d525c · inbound
Revitalizing Dense Material Segmentation: Stabilized Vision Transformers and the Generalization Paradox cites this paper.
Revitalizing Dense Material Segmentation: Stabilized Vision Transformers and the Generalization Paradox Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:40:24.465363Z
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.
Observation 8dfdee4d-b119-4ae4-b71d-cc5181e9848d · inbound
Physical Object Understanding with a Physically Controllable World Model cites this paper.
Physical Object Understanding with a Physically Controllable World Model Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T19:32:34.683112Z
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.