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Paper Citation Record · LEDGER

Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2112.07508.

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

pith.paper-citation-record.v1
2112.07508 v3

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 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T20:52:59.566447Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T20:53:15.292050Z

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 2e51ac3e-1769-437b-b6e9-a78efeac8c38 · inbound

Extracting Money Laundering Transactions from Quasi-Temporal Graph Representation cites this paper.

Extracting Money Laundering Transactions from Quasi-Temporal Graph Representation Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:53:15.293624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-13T20:52:59.566447Z digest=sha256:4c86206dd6f232414cf72942a890a16feb5b8fb539ada82da9f383c117c7b1ca

Observation 9ff2b4ac-060d-4f85-97f7-1e5f90f8a8fd · inbound

BlazingAML: High-Throughput Anti-Money Laundering (AML) via Multi-Stage Graph Mining cites this paper.

BlazingAML: High-Throughput Anti-Money Laundering (AML) via Multi-Stage Graph Mining Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:26:01.257746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T16:02:06.747576Z digest=sha256:926bdc750a66ea2dcde93a31720f5ddbb4a6c085ff28aea3f810b13d89643111