Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Model Monitoring and Robustness of In-Use Machine Learning Models: Quantifying Data Distribution Shifts Using Population Stability Index
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2302.00775.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T22:22:48.966148Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T14:21:07.043877Z
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 4cc345ec-dc91-4bde-ace3-29f2e5617333 · inbound
Improving Real-Time Concept Drift Detection using a Hybrid Transformer-Autoencoder Framework cites this paper.
Improving Real-Time Concept Drift Detection using a Hybrid Transformer-Autoencoder Framework Model Monitoring and Robustness of In-Use Machine Learning Models: Quantifying Data Distribution Shifts Using Population Stability Index
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:22:48.966148Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e932c2c-fb24-4ca2-a2a4-e023fb350d44 · inbound
Adversarial Evasion in Non-Stationary Malware Detection: Minimizing Drift Signals through Similarity-Constrained Perturbations cites this paper.
Adversarial Evasion in Non-Stationary Malware Detection: Minimizing Drift Signals through Similarity-Constrained Perturbations Model Monitoring and Robustness of In-Use Machine Learning Models: Quantifying Data Distribution Shifts Using Population Stability Index
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:21:07.046231Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation cc834a89-e743-4583-8c55-3ad54b329013 · inbound
When Drift Detectors cry Wolf: False Alarm Rates in continuous ML Monitoring cites this paper.
When Drift Detectors cry Wolf: False Alarm Rates in continuous ML Monitoring Model Monitoring and Robustness of In-Use Machine Learning Models: Quantifying Data Distribution Shifts Using Population Stability Index
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T18:21:42.080576Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.