Paper Citation Record · LEDGER

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection

As of 22 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2602.23599.

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

pith.paper-citation-record.v1
2602.23599 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:18:44.160124Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T22:27:30.692356Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T14:05:45.788468Z

Reference resolution

26 of 26 outbound references displayed

verified exact1
verified fuzzy0
unresolved23
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 527e10be-210a-48b7-9809-0c0444990013 · outbound

This paper cites In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD).

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD)

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.166294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90ecb5f2-15ac-4ae4-bb20-2115b9d4eb8f · outbound

This paper cites In: Proceedings of the 2020 5th International Conference on Machine Learning Technologies.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: Proceedings of the 2020 5th International Conference on Machine Learning Technologies

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.222158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b87d2056-e7e9-472c-9c52-0aa8cd88d2f2 · outbound

This paper cites Layer Normalization.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Layer Normalization

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.305052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd3c1844-b085-4cc3-8764-77c290b5a2ba · outbound

This paper cites The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.404904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8513b84d-a653-4660-81dd-9b5e20fe5a89 · outbound

This paper cites In: Meila, M., Zhang, T.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: Meila, M., Zhang, T

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.486331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bee507b-0cd7-4e4b-8007-7656f3843a80 · outbound

This paper cites In: International Conference on Learning Repre- sentations (2018), https://openreview.net/forum?id=rytstxWAW.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: International Conference on Learning Repre- sentations (2018), https://openreview.net/forum?id=rytstxWAW

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.576323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44ab249f-1800-4ac6-ae07-8b1b4e62d853 · outbound

This paper cites arXiv preprint arXiv:2405.19383 (2024), https://arxiv.org/abs/ 2405.19383.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection arXiv preprint arXiv:2405.19383 (2024), https://arxiv.org/abs/ 2405.19383

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.658290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af260894-82fe-40d8-afd7-f9052bf3b3ef · outbound

This paper cites Journal of Machine Learning Research23, 1421– 1478 (2022), https://jmlr.org/papers/v23/22-0567.html.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Journal of Machine Learning Research23, 1421– 1478 (2022), https://jmlr.org/papers/v23/22-0567.html

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.738948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c09886f-9503-45a0-9884-5f120410286b · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Fast Graph Representation Learning with PyTorch Geometric

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.870187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9c95e82-2d24-4a48-897e-771a1b7cc64d · outbound

This paper cites In: Teh, Y.W., Titterington, M.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: Teh, Y.W., Titterington, M

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:42.947846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d91bf138-d829-4959-9671-1bf4bac14a77 · outbound

This paper cites Synthesis Lectures on Artificial Intelligence and Machine Learning14, 1–159 (2020).

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Synthesis Lectures on Artificial Intelligence and Machine Learning14, 1–159 (2020)

Reference 11

Resolution: malformed identifier; no resolver link, observed 2026-08-02T20:18:43.013324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 186f369d-b202-4209-a98a-9a01a8fc14a9 · outbound

This paper cites Inductive Representation Learning on Large Graphs.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Inductive Representation Learning on Large Graphs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.068441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36f8b9ff-c27b-4c07-acdc-04b71d233e28 · outbound

This paper cites Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.145997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d178550a-cfd8-4eaa-8c11-4a8cb7859582 · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.211144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39fb4e4d-8cbe-46f2-a839-9e6513fd46cb · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Semi-Supervised Classification with Graph Convolutional Networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.322300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c0bbfd3-e69e-4feb-bd92-d9e92a070cbb · outbound

This paper cites In: 2024 IEEE 21st Consumer Communi- cations & Networking Conference (CCNC).

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: 2024 IEEE 21st Consumer Communi- cations & Networking Conference (CCNC)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.401888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb851103-8d3a-4047-aff4-1b6663cdf0dc · outbound

This paper cites In: Proceedings of the 26th International Conference on Multimodal Interaction.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: Proceedings of the 26th International Conference on Multimodal Interaction

Reference 17

Resolution: verified exact; doi, observed 2026-08-02T20:23:32.009927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0d6f70a1-5d32-4743-b874-e91ae9543db5 · outbound

This paper cites Scientific Reports14(2024).

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Scientific Reports14(2024)

Reference 18

Resolution: malformed identifier; no resolver link, observed 2026-08-02T20:18:43.522106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afef6b54-0637-410b-a6e8-44ca4d7abffc · outbound

This paper cites Temporal Graph Networks for Deep Learning on Dynamic Graphs.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Temporal Graph Networks for Deep Learning on Dynamic Graphs

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.583295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efe697ba-5da7-44aa-beda-82e410802521 · outbound

This paper cites PLOS ONE 10(3), e0118432 (2015).

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection PLOS ONE 10(3), e0118432 (2015)

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.701414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45cbd34e-e895-41d4-a982-7aad6f70a26d · outbound

This paper cites Graph Attention Networks.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Graph Attention Networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.790407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf86f711-abbe-4b71-afa5-be214d3abe9e · outbound

This paper cites In: International Conference on Learning Representations (2022), https://openreview.net/forum?id=XLxhEjKNbXj.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: International Conference on Learning Representations (2022), https://openreview.net/forum?id=XLxhEjKNbXj

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.857598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 355b502c-5617-465b-9cb9-de99ac61b818 · outbound

This paper cites Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:43.900651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54e9b57d-27e4-4626-be8b-c7dde5baf02b · outbound

This paper cites In: International Conference on Learn- ing Representations (2020), https://openreview.net/forum?id=BJe8pkHFwS.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: International Conference on Learn- ing Representations (2020), https://openreview.net/forum?id=BJe8pkHFwS

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:44.012345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 293b5057-5416-4ff6-84c1-e882c2a78e90 · outbound

This paper cites In: International Conference on Learning Representations (2020), https://openreview.net/forum? id=rkecl1rtwB.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: International Conference on Learning Representations (2020), https://openreview.net/forum? id=rkecl1rtwB

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:44.091541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da0400b8-c8bc-4c59-86f6-209ba51353fe · outbound

This paper cites In: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M., Lin, H.

Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection In: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M., Lin, H

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T20:18:44.160124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 41b50e3b-e395-467b-92ac-5639e9e9628a · inbound

From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems cites this paper.

From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems Normalisation and Initialisation Strategies for Graph Neural Networks in Blockchain Anomaly Detection

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-07-20T02:18:26.357570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.