Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Robust Subspace Recovery Layer for Unsupervised Anomaly Detection
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1904.00152.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:15:32.625999Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T17:33:45.430497Z
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 0fa56359-2e69-44f1-9fcd-ec256cc40d3e · inbound
MSD-LLM: Predicting Ship Detention in Port State Control Inspections with Large Language Model cites this paper.
MSD-LLM: Predicting Ship Detention in Port State Control Inspections with Large Language Model Robust Subspace Recovery Layer for Unsupervised Anomaly Detection
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:15:32.625999Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d9f5659d-2015-48d4-9e3f-f85e5075483e · inbound
Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation cites this paper.
Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation Robust Subspace Recovery Layer for Unsupervised Anomaly Detection
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T11:51:00.809047Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6c924539-d8b4-4f93-bb84-d21288bd4d44 · inbound
Landseer: Exploring the Machine Learning Defense Landscape cites this paper.
Landseer: Exploring the Machine Learning Defense Landscape Robust Subspace Recovery Layer for Unsupervised Anomaly Detection
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T17:33:45.431969Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.