Paper Citation Record · LEDGER

Characterizing and Detecting Money Laundering Activities on the Bitcoin Network

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1912.12060.

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

pith.paper-citation-record.v1
1912.12060 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:38:08.017273Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T11:46:12.888794Z

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 ff68121d-0001-4443-afc5-2d7131537b32 · inbound

Detecting Sybil Addresses in Blockchain Airdrops: A Subgraph-based Feature Propagation and Fusion Approach cites this paper.

Detecting Sybil Addresses in Blockchain Airdrops: A Subgraph-based Feature Propagation and Fusion Approach Characterizing and Detecting Money Laundering Activities on the Bitcoin Network

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T21:38:08.017273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e4ddd20-b102-44c2-ace8-33ce19ae6bee · inbound

Detecting Fraud in Financial Networks: A Semi-Supervised GNN Approach with Granger-Causal Explanations cites this paper.

Detecting Fraud in Financial Networks: A Semi-Supervised GNN Approach with Granger-Causal Explanations Characterizing and Detecting Money Laundering Activities on the Bitcoin Network

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T22:55:50.201776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c59011a-adca-4e17-b9dc-1d1c7c5bbeab · inbound

How Reliable Is the Multi-Input Heuristic for Bitcoin Address Clustering in Law Enforcement Contexts? cites this paper.

How Reliable Is the Multi-Input Heuristic for Bitcoin Address Clustering in Law Enforcement Contexts? Characterizing and Detecting Money Laundering Activities on the Bitcoin Network

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-07-09T11:46:12.890189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b70bc472-001f-4817-acc9-6a56dd0e90a7 · inbound

How Reliable Is the Multi-Input Heuristic for Bitcoin Address Clustering in Law Enforcement Contexts? cites this paper.

How Reliable Is the Multi-Input Heuristic for Bitcoin Address Clustering in Law Enforcement Contexts? Characterizing and Detecting Money Laundering Activities on the Bitcoin Network

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-13T06:43:20.760072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.