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Paper Citation Record · LEDGER

Variational Autoencoder for Anomaly Detection: A Comparative Study

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.13561.

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

pith.paper-citation-record.v1
2408.13561 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:58:42.155024Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T11:58:06.037405Z

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 461b61a7-b248-4e58-ba58-6725c8a8a1b5 · inbound

Bounding Distributional Shifts in World Modeling through Novelty Detection cites this paper.

Bounding Distributional Shifts in World Modeling through Novelty Detection Variational Autoencoder for Anomaly Detection: A Comparative Study

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T22:58:42.155024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:58:42.155024Z digest=sha256:dacfdb759a71d60f3792a939f21798e5380d541beb5ab3e78a753314bd16f47f

Observation b96cb706-8e80-4fa8-be22-dd1bcce3c8e3 · inbound

SwarmSense-DNN: A Trustworthy and Decentralized Neural Framework for Proactive Anomaly Defense in Consumer IoT cites this paper.

SwarmSense-DNN: A Trustworthy and Decentralized Neural Framework for Proactive Anomaly Defense in Consumer IoT Variational Autoencoder for Anomaly Detection: A Comparative Study

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-07-03T11:58:06.038896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T09:17:04.893967Z digest=sha256:94696dc20655b7ef75a281748024e28e49731215cbb8680af7e8cd4276704221