Paper Citation Record · LEDGER

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection

As of 7 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2606.08146.

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

pith.paper-citation-record.v1
2606.08146 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T19:48:52.564810Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:58:45.908231Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

verified exact5
verified fuzzy0
unresolved40
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1765eaca-741c-449f-a1e2-67a92eaf4c2c · outbound

This paper cites Qwen3-Max.https://qwen.ai/ research, 2025.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Qwen3-Max.https://qwen.ai/ research, 2025

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a21a8d6-22f4-4f65-8b71-5ced4589eea6 · outbound

This paper cites Claude code.https://www.anthropic.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Claude code.https://www.anthropic

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 7980fae2-8218-4cc5-855b-d37adee15d64 · outbound

This paper cites Claude opus 4.7 system card.https://www.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Claude opus 4.7 system card.https://www

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 5c7aeb29-87bc-4876-aff4-a7618eeb0378 · outbound

This paper cites Data mining for credit card fraud: A comparative study.Decision support systems, pages 602–613, 2011.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Data mining for credit card fraud: A comparative study.Decision support systems, pages 602–613, 2011

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 30bfcc89-7aa2-4dd9-8ef9-97569d443e9d · outbound

This paper cites Smote: synthetic minority over- sampling technique.Journal of artificial intelligence re- search, pages 321–357, 2002.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Smote: synthetic minority over- sampling technique.Journal of artificial intelligence re- search, pages 321–357, 2002

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

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Observation 551219ae-8914-4cee-a5d9-7461db0c7920 · outbound

This paper cites Xgboost: A scalable tree boosting system.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Xgboost: A scalable tree boosting system

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

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Observation 8d088bfb-26e1-4c65-bbb0-d6c28898640d · outbound

This paper cites Tlk: An in- dustrial internet of things attack detection method based on transformer-lstm-kelm.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Tlk: An in- dustrial internet of things attack detection method based on transformer-lstm-kelm

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 809a6287-2121-4ed6-bfc7-0965bfd621e7 · outbound

This paper cites Graph neural networks for financial fraud detection: a re- view.Frontiers of Computer Science, page 199609, 2025.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Graph neural networks for financial fraud detection: a re- view.Frontiers of Computer Science, page 199609, 2025

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

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Observation 537054d2-280e-417c-9547-4f9db003ba74 · outbound

This paper cites Learned lessons in credit card fraud detection from a practitioner perspective.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Learned lessons in credit card fraud detection from a practitioner perspective

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2777a897-a1da-4373-b3fb-cff63958da7c · outbound

This paper cites Credit card fraud de- tection: a realistic modeling and a novel learning strategy.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Credit card fraud de- tection: a realistic modeling and a novel learning strategy

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

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Observation 99c7f059-090e-4bfd-8b65-44e4e0079851 · outbound

This paper cites The relationship between precision-recall and roc curves.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection The relationship between precision-recall and roc curves

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 8cbd7220-76f9-4c60-9d37-dd2d3c2018e7 · outbound

This paper cites DeepSeek-V3.2.https : / / www.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection DeepSeek-V3.2.https : / / www

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 13744eaa-566b-4111-ac93-ae282064c59f · outbound

This paper cites Statistical comparisons of classifiers over multiple data sets.Journal of Machine learning research, pages 1–30, 2006.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Statistical comparisons of classifiers over multiple data sets.Journal of Machine learning research, pages 1–30, 2006

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f060fdce-c5bc-4720-a81f-98aa73b51e2e · outbound

This paper cites Telecom fraud detection based on large language models: A multi-role, multi-layer prompting strategy.Applied Sciences, page 544, 2026.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Telecom fraud detection based on large language models: A multi-role, multi-layer prompting strategy.Applied Sciences, page 544, 2026

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3269db11-515a-4e0f-b3ee-c7b7241defa8 · outbound

This paper cites Enhancing graph neural network-based 15 fraud detectors against camouflaged fraudsters.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Enhancing graph neural network-based 15 fraud detectors against camouflaged fraudsters

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 5b7e3d6a-373c-4072-8f08-d1a2f5b29821 · outbound

This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-07-02T21:17:25.049143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 65b50180-8e6d-4e13-8fde-9ec6302c8002 · outbound

This paper cites Efficient and robust automated machine learning.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Efficient and robust automated machine learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

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Observation feef9485-a51e-47f6-bf61-db27563b02ad · outbound

This paper cites The global state of scams 2025 report.https://www.gasa.org/, 2025.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection The global state of scams 2025 report.https://www.gasa.org/, 2025

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 6090a72f-31bc-48b4-aff5-0a2740c635ae · outbound

This paper cites Why do tree-based models still outperform deep learning on typi- cal tabular data? InNeurIPS, pages 507–520, 2022.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Why do tree-based models still outperform deep learning on typi- cal tabular data? InNeurIPS, pages 507–520, 2022

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 7ab9fce2-24ce-46ac-b988-91f22b178c80 · outbound

This paper cites Fraud Dataset Benchmark and Applications.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Fraud Dataset Benchmark and Applications

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:17:25.058728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 80547a67-cce4-4521-95a4-0d59e70cce40 · outbound

This paper cites Learning from imbalanced data.IEEE Transactions on knowledge and data engineer- ing, pages 1263–1284, 2009.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Learning from imbalanced data.IEEE Transactions on knowledge and data engineer- ing, pages 1263–1284, 2009

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb91dd31-f62b-4f7a-aca8-70b2e36f4a92 · outbound

This paper cites FACTGUARD: event-centric and commonsense-guided fake news detection.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection FACTGUARD: event-centric and commonsense-guided fake news detection

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 983c0702-2d7a-4383-a6fb-17e596a04eb2 · outbound

This paper cites Data interpreter: An llm agent for data sci- ence.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Data interpreter: An llm agent for data sci- ence

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 705cbb46-13a5-42f8-9b47-46bc1d395b62 · outbound

This paper cites Sequence classification for credit-card fraud detection.Expert systems with applica- tions, pages 234–245, 2018.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Sequence classification for credit-card fraud detection.Expert systems with applica- tions, pages 234–245, 2018

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation f6953e09-2af9-43cd-ae7a-b3eed96dd27f · outbound

This paper cites Pick and choose: A gnn-based imbalanced learning approach for fraud detection.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Pick and choose: A gnn-based imbalanced learning approach for fraud detection

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 5f39f296-96b8-407b-9f22-adbc8b75c118 · outbound

This paper cites Paysim: A financial mobile money simulator for fraud de- tection.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Paysim: A financial mobile money simulator for fraud de- tection

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

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Observation 58df24be-260f-403b-97d3-fe8b62d0af38 · outbound

This paper cites Credit card fraud detection using machine learning: A survey.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Credit card fraud detection using machine learning: A survey

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:17:25.046810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d3572872-c7b4-4b90-98ac-52ae8dd1c492 · outbound

This paper cites Comparison of the predicted and ob- served secondary structure of t4 phage lysozyme.Biochim- ica et Biophysica Acta (BBA)-Protein Structure, pages 442– 451, 1975.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Comparison of the predicted and ob- served secondary structure of t4 phage lysozyme.Biochim- ica et Biophysica Acta (BBA)-Protein Structure, pages 442– 451, 1975

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 3c633ee8-891c-42ab-95cc-b2f868cd0f56 · outbound

This paper cites LLaMA-3.3-70B.https://www.llama.com,.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection LLaMA-3.3-70B.https://www.llama.com,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85f63baa-4b75-4438-bb77-9996c739d56d · outbound

This paper cites GPT-5.4.https://openai.com, 2026.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection GPT-5.4.https://openai.com, 2026

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 1f003d1f-3032-4d09-aace-1a9449b040c3 · outbound

This paper cites Johnson, and Gianluca Bontempi.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Johnson, and Gianluca Bontempi

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 7672e079-54a1-4d07-bc2d-67ff4d80d0b7 · outbound

This paper cites Automatic prompt optimization with ”gradient descent” and beam search.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Automatic prompt optimization with ”gradient descent” and beam search

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e83a4329-1b18-4f8e-a394-46ab3ede734d · outbound

This paper cites Sequential fraud de- tection for prepaid cards using hidden markov model diver- gence.Expert Systems with Applications, pages 235–251,.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Sequential fraud de- tection for prepaid cards using hidden markov model diver- gence.Expert Systems with Applications, pages 235–251,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dd3b263-be64-4487-9c88-45661ab59a14 · outbound

This paper cites Digital deception: Genera- tive artificial intelligence in social engineering and phishing.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Digital deception: Genera- tive artificial intelligence in social engineering and phishing

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation b4a33e06-84b6-472e-8f7b-442dd66883dc · outbound

This paper cites Reflexion: language agents with verbal reinforcement learning.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Reflexion: language agents with verbal reinforcement learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 5bd3ffb2-2c8c-434e-9992-8adf3d17d041 · outbound

This paper cites Tabular data: Deep learning is not all you need.Information fusion, pages 84– 90, 2022.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Tabular data: Deep learning is not all you need.Information fusion, pages 84– 90, 2022

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 6c5187dd-8b3a-46a9-a1bc-e3261b177746 · outbound

This paper cites MIT press Cambridge, 1998.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection MIT press Cambridge, 1998

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Unavailable: canonical work link unavailable.

Observation cdb44926-7f47-4e02-a8e2-9659fd6ef971 · outbound

This paper cites FLAML: A fast and lightweight automl library.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection FLAML: A fast and lightweight automl library

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b29d6c3-a4fe-460b-ba82-ce81c15b3fd4 · outbound

This paper cites A semi-supervised graph attentive network for financial fraud detection.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection A semi-supervised graph attentive network for financial fraud detection

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 8bfcc596-d4cf-46d7-aed0-92b2c67db0bc · outbound

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

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T21:17:25.043924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2eee3e8d-1405-4ccd-8d45-8f404fb70094 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-07-02T21:17:25.051794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 369b533b-9de1-46be-8c48-dbbe47801734 · outbound

This paper cites Semi- supervised credit card fraud detection via attribute-driven graph representation.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Semi- supervised credit card fraud detection via attribute-driven graph representation

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation b9200d79-2405-4884-a496-de2ccb9c44ec · outbound

This paper cites an unresolved cited work.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Unresolved cited work

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 352ffc70-7154-4c8b-a173-143ca7227144 · outbound

This paper cites Random forest for credit card fraud detection.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Random forest for credit card fraud detection

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Observation 1edcc6dd-ed75-4a8b-8c29-717b4ee4de57 · outbound

This paper cites Narasimhan, and Yuan Cao.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection Narasimhan, and Yuan Cao

Reference 45

Resolution: unresolved; no resolver link, observed 2026-06-27T19:48:52.564810Z

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Unavailable: canonical work link unavailable.

Observation 76f7da30-0c1b-47d8-a3b2-ca1b90382c2c · outbound

This paper cites A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection.

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:17:25.055343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation fbdcc08a-7230-47a5-9eea-bb19d24bf4b8 · inbound

Toward Auditable Fraud Detection: Combining Graph Features, Model Explanations, and Agentic Case Investigation cites this paper.

Toward Auditable Fraud Detection: Combining Graph Features, Model Explanations, and Agentic Case Investigation SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T12:58:45.908231Z

Source-reported events for the cited work

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