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Paper Citation Record · LEDGER

Network Traffic Anomaly Detection Using Recurrent Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1803.10769.

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

pith.paper-citation-record.v1
1803.10769 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:00:09.808123Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:33:59.217636Z

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 8d097c49-da84-48c7-9d77-eda463b44634 · inbound

Mamba Adaptive Anomaly Transformer with association discrepancy for time series cites this paper.

Mamba Adaptive Anomaly Transformer with association discrepancy for time series Network Traffic Anomaly Detection Using Recurrent Neural Networks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-08T12:00:09.808123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:00:09.808123Z digest=sha256:d289d9a65086cad8be693e83e3119099b20a8bd4be925423c87ffd556e1709fb

Observation 228f9553-3e44-4617-bc0e-e87e33fc3d1a · inbound

AI/ML for 5G and Beyond Cybersecurity cites this paper.

AI/ML for 5G and Beyond Cybersecurity Network Traffic Anomaly Detection Using Recurrent Neural Networks

Reference 1701

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T14:33:59.330745Z

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.

source=pdf_text observed=2026-08-07T14:33:58.891888Z digest=sha256:99999548d3ef2b28375ab2e40a12777380376e511b617816c0fb41b8a2b21fd2