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Paper Citation Record · LEDGER

Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2202.07857.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2202.07857 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:53:47.831866Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-17T06:59:12.111188Z

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 ed46271a-d12e-4b7e-8ed5-4d0d8b002d87 · inbound

Stealing Training Graphs from Graph Neural Networks cites this paper.

Stealing Training Graphs from Graph Neural Networks Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T18:53:47.831866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:53:47.831866Z digest=sha256:1389c22e84507c54a2a290ddb8a1638d96776a1a0490a6637c510a8ffc2cb499

Observation f50b86b9-1b31-4789-adcd-a7b9044e4c58 · inbound

A Generalizable Anomaly Detection Method in Dynamic Graphs cites this paper.

A Generalizable Anomaly Detection Method in Dynamic Graphs Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T10:37:43.604372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:37:43.604372Z digest=sha256:8ff630993dc9e3a77eeaab938df27013119d5c0de6cf7763ab962c0bb435e1c5

Observation f4c9eedc-70c8-4744-8c44-465a8cdcdc8d · inbound

Multivariate Time Series Anomaly Detection by Capturing Coarse-Grained Intra- and Inter-Variate Dependencies cites this paper.

Multivariate Time Series Anomaly Detection by Capturing Coarse-Grained Intra- and Inter-Variate Dependencies Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T17:01:34.974107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:01:34.974107Z digest=sha256:95046ba70fcf6ec45b339c1304f290f3210e6dbd9f9ead7b2a637274c824fb7f

Observation d716825e-cc52-4ae5-9c82-111d27a3f677 · inbound

A Problem-Oriented Taxonomy of Evaluation Metrics for Time Series Anomaly Detection cites this paper.

A Problem-Oriented Taxonomy of Evaluation Metrics for Time Series Anomaly Detection Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-17T06:59:12.114373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-17T06:57:30.549902Z digest=sha256:ce3b0085efe2c5361f7303f6a554585eda17dcd498dbe6317b118443de534bcd

Observation d06a3bb7-aca1-4314-979f-63fa63883ab8 · inbound

Knowledge-Assisted Multi-Graph Dependency Learning for Multivariate Time Series Anomaly Detection in Multi-Stage Industrial Processes cites this paper.

Knowledge-Assisted Multi-Graph Dependency Learning for Multivariate Time Series Anomaly Detection in Multi-Stage Industrial Processes Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-01T22:20:53.378290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:20:53.378290Z digest=sha256:ce0c9814aed3fd8d0841adf18093cb67d098d9d2288aafc97c348f05164c4080

Observation cb60ec2f-34a9-41b2-bdd1-85de68f0c1ec · inbound

Domain-Prior-Regularized Graph Modeling for Anomaly Detection in Cyber-Physical Systems cites this paper.

Domain-Prior-Regularized Graph Modeling for Anomaly Detection in Cyber-Physical Systems Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-01T03:22:37.109556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:22:37.109556Z digest=sha256:daf39b0cf9837bbaae153d572043d18546fd186149379730ad4d8ed32fb83105