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Paper Citation Record · LEDGER

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection

As of 23 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2412.07437.

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

pith.paper-citation-record.v1
2412.07437 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:53:41.286213Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

  • verified exact8
  • verified fuzzy8
  • unresolved4
  • parse uncertain0
  • malformed identifier4
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d6919c20-966a-480d-8a82-f51cfffcc7cd · outbound

This paper cites Fraud detection sys- tem: A survey.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Fraud detection sys- tem: A survey

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.471052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:39.905124Z digest=sha256:cc4563b18d67801cc0f55cb8a7e50eff01165b1dc5a203a57ab8ada6bd867ebb

Observation 75f2a49f-2d53-4803-80cc-fec38a5acaec · outbound

This paper cites Credit Card Fraud Detection Using XGBoost Algorithm.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Credit Card Fraud Detection Using XGBoost Algorithm

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.417982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:39.935098Z digest=sha256:bea01c8a75c6632c6809ab4fa12226725e36d494840586f33f0a09294f65323c

Observation dc55a8f1-efe4-44af-bef7-578245f0d299 · outbound

This paper cites Survey of Credit Card Anomaly and Fraud Detection Using Sampling Techniques.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Survey of Credit Card Anomaly and Fraud Detection Using Sampling Techniques

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-11T18:53:44.353170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.134077Z digest=sha256:f2a87a2d32e04bafd1fcf3a6a4c5a8f27e1dd5f0da83e087cab308adc44fafb2

Observation e8bfa658-30e2-4bb8-836a-8ff11e828caa · outbound

This paper cites Data mining for credit card fraud: A comparative study.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Data mining for credit card fraud: A comparative study

Reference 4

Resolution
verified exact
doi, observed 2026-08-11T18:53:42.184869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.148624Z digest=sha256:1c3622eb581b4d738aa506098f36fcbb6912790cb48dddfc3a11b4bd75cc645d

Observation a5823a8e-cdcc-470d-ada5-2a8d76f153b8 · outbound

This paper cites Random forests.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Random forests

Reference 5

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unresolved
no resolver link, observed 2026-08-11T18:53:40.194840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:53:40.194840Z digest=sha256:7ad4f68d03205adcda34c4de978821474ed68426b03f5b59a35b6dbcae28690a

Observation 5eb8e31b-cd66-4dc8-811d-b19eb976aadd · outbound

This paper cites Lost, stolen or skimmed: Overcoming credit card fraud in South Africa.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Lost, stolen or skimmed: Overcoming credit card fraud in South Africa

Reference 6

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malformed identifier
raw_fallback, observed 2026-08-11T18:53:44.205527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.257574Z digest=sha256:1e6353f1546b98f6e25f1474e7ea5a9c3650d9a01914d0102a3bb388885a4a72

Observation 55772e85-268a-4547-8523-2044bda56407 · outbound

This paper cites SMOTE: Synthetic Minority Over-sampling Technique.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection SMOTE: Synthetic Minority Over-sampling Technique

Reference 7

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malformed identifier
raw_fallback, observed 2026-08-11T18:53:44.107879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.345195Z digest=sha256:1b75fa0adb36a66ea8076bbe38e01efa26544a1b3134c792a5e3983ca0e6e72b

Observation fad6ba5a-2ed9-4fb3-9451-ec55d6c78de4 · outbound

This paper cites SMOTE: Synthetic Minority Over-sampling Technique.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection SMOTE: Synthetic Minority Over-sampling Technique

Reference 8

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T18:53:43.934344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.426836Z digest=sha256:914213467f278921607f519794751328c5a49a43f5e93447177e410e8f201ec4

Observation 21df9c9a-d21d-44c6-932d-1d29014d78a2 · outbound

This paper cites Xgboost: A scalable tree boosting system.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Xgboost: A scalable tree boosting system

Reference 9

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unresolved
no resolver link, observed 2026-08-11T18:53:40.435378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:53:40.435378Z digest=sha256:d1414968ef8e1521870b85cf39683fc9917e4acc26eb3e3b1a17f031bebf92e4

Observation af709bf0-80b1-4ff8-9708-164c970c01b7 · outbound

This paper cites The classification performance of ensemble decision tree classifiers: a case study of detecting fraud in credit card transactions.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection The classification performance of ensemble decision tree classifiers: a case study of detecting fraud in credit card transactions

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.813156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.448813Z digest=sha256:0f57e7511d47096f41e10155298a16af1f3343053e42fe7c94caa1866884110d

Observation f12c0dc7-f65a-41fd-9516-4b9824fed3a5 · outbound

This paper cites Generating multi-label discrete patient records using generative adversarial networks.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Generating multi-label discrete patient records using generative adversarial networks

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.712037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.473340Z digest=sha256:c340105e605a4d8083e168c73dcf667d30091d3bb9c1e71056be52ce3c5ad2f2

Observation 73d8ade2-d3c8-4a5b-a2b2-f1e293ea2270 · outbound

This paper cites Effective data generation for imbalanced learning using conditional generative adversarial networks.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Effective data generation for imbalanced learning using conditional generative adversarial networks

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.575081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.487971Z digest=sha256:451f5101bd3fc2c1721b2c26c221b088c159d12350d162b71fcb90fe608e9ee4

Observation 571f86fb-4eb3-4327-a5aa-f89d131b3be0 · outbound

This paper cites A novel method for detecting credit card fraud problems.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection A novel method for detecting credit card fraud problems

Reference 13

Resolution
verified exact
doi, observed 2026-08-11T18:53:41.973161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.525138Z digest=sha256:f17f0b6c230d3bf618cd8c6f5f9c3061ddaacfaf178624ec2d7f6918204fe772

Observation 54ca73b5-d3b0-44d4-a799-5995430b0b15 · outbound

This paper cites Fraud De- tection in Banking Data by Machine Learning Techniques.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Fraud De- tection in Banking Data by Machine Learning Techniques

Reference 15

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metadata mismatch
raw_fallback, observed 2026-08-11T18:53:42.975445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.718120Z digest=sha256:491290f10335ddad6a989bedb0aa59b0c1a2ee9488068ddbd9796f3c1b032f8e

Observation 1bdb48c4-8c8e-4889-ba06-4ff4766cd35d · outbound

This paper cites Fraud detection: Intention- ality and deception in cognition.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Fraud detection: Intention- ality and deception in cognition

Reference 16

Resolution
verified exact
raw_fallback, observed 2026-08-11T18:53:42.760301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.734870Z digest=sha256:df613120d99aca7df91e6988ada22cc4df872479f76ee3a084243205d157f7a7

Observation a6b6a0b1-c539-4178-bf11-b39e853a625f · outbound

This paper cites Keep it simple: random oversampling for imbalanced data.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Keep it simple: random oversampling for imbalanced data

Reference 17

Resolution
verified exact
raw_fallback, observed 2026-08-11T18:53:42.596798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.784873Z digest=sha256:dddc27b531d20b51929197e8f3013f93948e63cf0aee434fb4e75d029bb3f1a4

Observation 11b5d113-dc72-4ed3-8933-f72e02b7c768 · outbound

This paper cites GAN-based imbalanced data intrusion detection system.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection GAN-based imbalanced data intrusion detection system

Reference 18

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malformed identifier
no resolver link, observed 2026-08-11T18:53:40.820477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:53:40.820477Z digest=sha256:bd383a64cd46f9457ee3c4fe1fbeabce7a9193eefc3b5fb1493b05d45ddc8b60

Observation 3be2b4ac-1228-4831-9ea0-e6428b6f6f30 · outbound

This paper cites Credit-Card-Fraud-Prediction- Using-XGBoost -An-Ensemble-Learning-Approach.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Credit-Card-Fraud-Prediction- Using-XGBoost -An-Ensemble-Learning-Approach

Reference 20

Resolution
verified exact
doi, observed 2026-08-11T18:53:41.764751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.914746Z digest=sha256:3b28d51adc25a6edad094db9d692277c9aa0549234a53cae54b63061271966f0

Observation 2d72ad28-b02b-4359-bdd2-b440171d112b · outbound

This paper cites A Comparison Study of Credit Card Fraud Detection: Supervised versus Unsupervised.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection A Comparison Study of Credit Card Fraud Detection: Supervised versus Unsupervised

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:53:42.342804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:41.024749Z digest=sha256:06061ea7d9f88d6043b9cab731dd4abad8143fc1b990782508f459d2b99491a8

Observation 045cc142-02f4-4a34-8710-d29181238b2c · outbound

This paper cites Credit Card Fraud Detection.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Credit Card Fraud Detection

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.474759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:41.064744Z digest=sha256:0bb702a4a605750df400557e8ac03ae730e0056c0aecfeeb953baa20db1a7fd7

Observation 866aa834-18b0-4469-b521-0f7f96bcbfbc · outbound

This paper cites Data leakage inflates prediction performance in connectome- based machine learning models.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Data leakage inflates prediction performance in connectome- based machine learning models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-11T18:53:41.104745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:53:41.104745Z digest=sha256:752578684585d5e0986ecce967047252095d18c490487668fd47f9a973e1fc71

Observation fdc4e736-f787-4c9a-a759-58b29700287c · outbound

This paper cites Hazards of data leakage in machine learning: a study on classification of breast cancer using deep neural networks.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Hazards of data leakage in machine learning: a study on classification of breast cancer using deep neural networks

Reference 24

Resolution
verified exact
doi, observed 2026-08-11T18:53:41.487116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:41.144747Z digest=sha256:640cde206e93775980e03f88e05f3b69b45ea075e05a01fcad43c4b386efbcf9

Observation 4cf62123-40d7-4dfd-b1f1-ed2e3377a0fa · outbound

This paper cites Semi-supervised anomaly detection for EEG waveforms using deep belief nets.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Semi-supervised anomaly detection for EEG waveforms using deep belief nets

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-11T18:53:43.416504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:41.219800Z digest=sha256:0e31c891f2bf174aa25ed276fe9495b58823740c6b311fb89106afe94bb97a19

Observation 15f96cf3-20ee-48b4-9504-50f70ef37fd3 · outbound

This paper cites Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data

Reference 26

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no resolver link, observed 2026-08-11T18:53:41.286213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:53:41.286213Z digest=sha256:b5a2904b25906abf6971592025cf02d37bdf2ca628563b3b1c6dcf23f93fdbbe

Observation 0c65eeb5-46ed-4d08-a7ef-3023b983c142 · outbound

This paper cites an unresolved cited work.

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection Unresolved cited work

Reference 492

Resolution
verified exact
raw_fallback, observed 2026-08-11T18:53:43.263961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T18:53:40.050284Z digest=sha256:048dc3aa00cc3e1b7d53a361f60dd0fe5290d37b183dd66bad536c35b2ffb96f

Pith citing papers

No inbound Pith citation observations are available.