Paper Citation Record · LEDGER

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems

As of 13 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 4 inbound Pith citation observations for arXiv:2412.07027.

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

pith.paper-citation-record.v1
2412.07027 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:53:14.086659Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:18:29.363394Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T04:33:59.062245Z

Reference resolution

16 of 16 outbound references displayed

verified exact1
verified fuzzy10
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b8790bdf-e2d6-461f-a3e0-d82e694fc73f · outbound

This paper cites Anti-Money Laundering (AML) Information Technology Strategies in Cross-Border Payment Systems,.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Anti-Money Laundering (AML) Information Technology Strategies in Cross-Border Payment Systems,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.355044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d1f59703-9141-45b4-aa47-987efe07aee2 · outbound

This paper cites The power of data: Transforming compliance with anti- money laundering measures in domestic and cross-border payments,.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems The power of data: Transforming compliance with anti- money laundering measures in domestic and cross-border payments,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.338698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation de5f5bb8-d591-4841-977d-1319cebd90d2 · outbound

This paper cites Improving client risk classification with machine learning to increase anti-money laundering detection efficiency,.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Improving client risk classification with machine learning to increase anti-money laundering detection efficiency,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.324382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ad7fc9e9-a66b-4cb0-8c78-12cfb43f575b · outbound

This paper cites Transformers in Opinion Mining: Addressing Semantic Complexity and Model Challenges in NLP,.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Transformers in Opinion Mining: Addressing Semantic Complexity and Model Challenges in NLP,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.309884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c06264d2-f411-4b55-bdf6-4c7f29e73a1e · outbound

This paper cites Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T15:53:14.032214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5d76882-5a87-417f-8c31-5691cd67974e · outbound

This paper cites Artificial Intelligence for Enhanced Anti-Money Laundering and Asset Recovery: A New Frontier in Financial Crime Prevention,.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Artificial Intelligence for Enhanced Anti-Money Laundering and Asset Recovery: A New Frontier in Financial Crime Prevention,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.295674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fa2a22c6-e769-4cee-9ba9-a33f80640951 · outbound

This paper cites Anti-money laundering main techniques and tools: a review of the literature,.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Anti-money laundering main techniques and tools: a review of the literature,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.279290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b25a423e-0fb0-41eb-b496-a0eeec9692ba · outbound

This paper cites Wasserstein Distance-Weighted Adversarial Network for Cross-Domain Credit Risk Assessment.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Wasserstein Distance-Weighted Adversarial Network for Cross-Domain Credit Risk Assessment

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T15:53:14.046923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a826301-3760-4f96-a87c-070ba2c4d199 · outbound

This paper cites Using artificial intelligence to counter money laundering and terrorist financing,.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Using artificial intelligence to counter money laundering and terrorist financing,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.263681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8935f1bf-8c93-4c28-9dbf-376ba61725cc · outbound

This paper cites The Impact of Large Interest Rate Differentials between China and the US on the Role of Chinese Monetary Policy--Based on Data Model Analysis.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems The Impact of Large Interest Rate Differentials between China and the US on the Role of Chinese Monetary Policy--Based on Data Model Analysis

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.249111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5ea697db-0b62-484d-8718-5844a7128564 · outbound

This paper cites Optimizing YOLOv5s Object Detection through Knowledge Distillation algorithm.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Optimizing YOLOv5s Object Detection through Knowledge Distillation algorithm

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T15:53:14.061253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b1b2802-5c87-42ad-bd42-9b5f2d37902f · outbound

This paper cites Transaction monitoring in anti-money laundering: A qualitative analysis and points of view from industry,.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Transaction monitoring in anti-money laundering: A qualitative analysis and points of view from industry,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.234389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d6b3f36d-3dbb-41a5-9cfc-31ebd23c23da · outbound

This paper cites Efficient and Aesthetic UI Design with a Deep Learning-Based Interface Generation Tree Algorithm.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Efficient and Aesthetic UI Design with a Deep Learning-Based Interface Generation Tree Algorithm

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T15:53:14.070950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e665fa72-11bf-4ae2-8026-14b082dc4a4e · outbound

This paper cites Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T15:53:14.075002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ac621c9-d4d7-4c3b-ad21-0847bcbaa749 · outbound

This paper cites A Hybrid CNN-LSTM Model for Enhancing Bond Default Risk Prediction.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems A Hybrid CNN-LSTM Model for Enhancing Bond Default Risk Prediction

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:14.220411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1b8a6819-bc89-4fc7-af63-10c3c2add07e · outbound

This paper cites Enhancing Anti-Money Laundering Efforts with Network-Based Algorithms.

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems Enhancing Anti-Money Laundering Efforts with Network-Based Algorithms

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-12T15:53:14.136899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation 118de370-e529-4666-ad43-46e7faf2aea3 · inbound

Machine Learning Techniques for Pattern Recognition in High-Dimensional Data Mining cites this paper.

Machine Learning Techniques for Pattern Recognition in High-Dimensional Data Mining Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T11:18:29.363394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5862092a-189c-45f2-a505-22e6b4de817b · inbound

Dynamic Scheduling Strategies for Resource Optimization in Computing Environments cites this paper.

Dynamic Scheduling Strategies for Resource Optimization in Computing Environments Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T05:40:19.707171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2306ba41-c4ac-400c-b751-5f760cbd986e · inbound

Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithms cites this paper.

Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithms Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T04:59:39.978009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44daf93e-9309-4e9f-b269-be53ba01f24b · inbound

Optimizing Large Language Models with an Enhanced LoRA Fine-Tuning Algorithm for Efficiency and Robustness in NLP Tasks cites this paper.

Optimizing Large Language Models with an Enhanced LoRA Fine-Tuning Algorithm for Efficiency and Robustness in NLP Tasks Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-11T04:33:59.071097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.