Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2311.14897.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T13:10:41.956818Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T11:01:30.663330Z
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 8695b823-92ed-4045-80ce-e4dd68b8a606 · inbound
Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection cites this paper.
Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T13:10:41.956818Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3d73880a-84ac-4439-b0d0-7adbd9a0a09c · inbound
Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties cites this paper.
Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:07:51.255617Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fa9b6c10-e067-41c3-b5cf-cae4957f4500 · inbound
Learning Discriminative Signed Distance Functions from Multi-scale Level-of-detail Features for 3D Anomaly Detection cites this paper.
Learning Discriminative Signed Distance Functions from Multi-scale Level-of-detail Features for 3D Anomaly Detection Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T11:01:30.665841Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 01f1d7b0-15a2-462d-8be7-c991e783fa27 · inbound
Learning Discriminative Signed Distance Functions from Multi-scale Level-of-detail Features for 3D Anomaly Detection cites this paper.
Learning Discriminative Signed Distance Functions from Multi-scale Level-of-detail Features for 3D Anomaly Detection Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T05:55:31.311584Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.