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Paper Citation Record · LEDGER

An Efficient One-Class SVM for Anomaly Detection in the Internet of Things

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.11146.

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

pith.paper-citation-record.v1
2104.11146 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 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:12:55.737548Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T03:32:01.474378Z

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 433d5df9-f1b1-41f2-b57a-9720b17f6402 · inbound

Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback cites this paper.

Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback An Efficient One-Class SVM for Anomaly Detection in the Internet of Things

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-19T03:32:01.476700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T03:30:00.958369Z digest=sha256:7d9da7045f29d608bf82546dcd165b6af59a3a9213d5e82138cb9707114aacf5

Observation 8d149c29-9f04-47c7-ad4c-c8b9fb3dc707 · inbound

Flow-Based Detection and Identification of Zero-Day IoT Cameras cites this paper.

Flow-Based Detection and Identification of Zero-Day IoT Cameras An Efficient One-Class SVM for Anomaly Detection in the Internet of Things

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T16:12:55.737548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:12:55.737548Z digest=sha256:9efb015ff68350a7e56b88c6827b52549d2e92d1f3241c32f9073c60eec6b59e