Pith. sign in

Paper Citation Record · LEDGER

Finding Money Launderers Using Heterogeneous Graph Neural Networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.13499.

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

pith.paper-citation-record.v1
2307.13499 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 2026-08-07T11:54:17.685628Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:26:01.244769Z

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 0958bb1b-89ce-46c8-89d2-53169e9c6274 · inbound

Regulatory Graphs and GenAI for Real-Time Transaction Monitoring and Compliance Explanation in Banking cites this paper.

Regulatory Graphs and GenAI for Real-Time Transaction Monitoring and Compliance Explanation in Banking Finding Money Launderers Using Heterogeneous Graph Neural Networks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T11:54:17.685628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:54:17.685628Z digest=sha256:7d325b1ca28fadccce77cba741c72b61b6c725cdcebe649487a61718e38afdce

Observation df3e8987-3d98-419d-9d26-2324f3f687c1 · 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 Finding Money Launderers Using Heterogeneous Graph Neural Networks

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:26:01.247138Z

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=2026-05-10T16:02:06.747576Z digest=sha256:17baffd0af40d09119641f0462138237bf89c7dfc6c40f910fff96b2af33d982