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Paper Citation Record · LEDGER

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments

As of 15 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 2 inbound Pith citation observations for arXiv:2508.19932.

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

pith.paper-citation-record.v1
2508.19932 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T20:35:29.338034Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T07:06:18.728116Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-20T22:33:48.596725Z

Reference resolution

24 of 24 outbound references displayed

  • verified exact10
  • verified fuzzy10
  • unresolved1
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bfe2f6e1-f178-4b38-9f4a-d4b0566090c8 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Gemini: A Family of Highly Capable Multimodal Models

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-05-18T20:36:50.242481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:7aa782c5b61234f7950bcc23dca751efe8a03f9f0b767e0d2d5e9198327994ea

Observation 364c50bb-7b03-4990-8a97-5cf04dc4db94 · outbound

This paper cites an unresolved cited work.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-05-18T20:36:50.925523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:d52d0628358f4043a4867ede6c9a580babcb9743444629ec002e652f3c0d5c05

Observation cbae59ea-a7fc-46d0-8a21-ebf03257ba4b · outbound

This paper cites International scammers steal over $1 trillion in 12 Months in global state of scams report 2024, GASA.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments International scammers steal over $1 trillion in 12 Months in global state of scams report 2024, GASA

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.929044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:741b6d34e35b337c582e6a65af061cc82dd5b87ef8c23ac0029862959dc8e15e

Observation 799a5842-7720-48ed-868a-fb0c9b31bcee · outbound

This paper cites Holistic Safety and Responsibility Evaluations of Advanced AI Models.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Holistic Safety and Responsibility Evaluations of Advanced AI Models

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T20:36:50.237159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:b764eb240500e59e9a4a4aa90afebe041466308c8e785a01a1f307a2b7fe79dc

Observation 29d2086a-273b-4551-8cc4-8d3b868e8a3b · outbound

This paper cites Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-18T20:36:50.232235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:21aa937b2a4221699d6d178f4747c0a1359da4cdf890d93364859b422c6d55ff

Observation 43ce6c4d-e234-45c0-b24e-69e936ebce8a · outbound

This paper cites A survey of information extraction based on deep learning.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments A survey of information extraction based on deep learning

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.922273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:609de23a8a1d65cd94aa65d05829522f6f1aab533505d1fcecf0731218893d22

Observation dcbc63a6-81a9-4d20-8a06-be4a8bfc3817 · outbound

This paper cites Using large language models for goal-oriented dialogue systems.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Using large language models for goal-oriented dialogue systems

Reference 7

Resolution
verified exact
doi, observed 2026-05-18T20:36:50.059001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:b5c98eb6e40253cca728333e122b798777fc37c1655ede27ed8e9ac44c8f2d16

Observation 6433d2a9-4b5a-46f4-b5a5-a2e5f1c3da3c · outbound

This paper cites Artificial Intelligence and machine learning in fraud detection for digital payments.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Artificial Intelligence and machine learning in fraud detection for digital payments

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.947863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:a40730568e4b88412f4b29b20691db608e470c94a2384ad2c7a160a4602a6c51

Observation 9cdce9d6-999c-4b25-93a6-edbcef3f7362 · outbound

This paper cites Trust & Safety of LLMs and LLMs in Trust & Safety.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Trust & Safety of LLMs and LLMs in Trust & Safety

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-18T20:36:50.285951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:e52ca0ceccc61c35a25de36b1289e3daf59b5a23cbdb667afdfd56c2506c6a55

Observation 0824facd-3362-40a1-ac95-aca68f456ef3 · outbound

This paper cites Enhancing Payment Ecosystems with AI/ML: Real- Time Analytics for Fraud Prevention and User Insights.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Enhancing Payment Ecosystems with AI/ML: Real- Time Analytics for Fraud Prevention and User Insights

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.936581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:457198e660159c43b5337ef6bb4045f9eb8096729470fb97c4ac188cc6aaa448

Observation dc170bb0-764f-49ac-81c3-71f9b54ebd8f · outbound

This paper cites Safety by Measurement: A Systematic Literature Review of AI Safety Evaluation Methods.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Safety by Measurement: A Systematic Literature Review of AI Safety Evaluation Methods

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-18T20:36:50.249177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:48669d4d0a4765acd6f9fa9d9e869919511b47e47c5f2e94a754a218d9adb547

Observation 9da63934-2330-48fc-a9c6-0ad8e789d7aa · outbound

This paper cites Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-18T20:36:50.269769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:9807f3cbc44df9b710542723d13cb3ce215bf5d7fe3077cf02d94b6d3b029a37

Observation 38e268b4-87b5-403f-92b5-9b0c9bdd8ba7 · outbound

This paper cites Responsible artificial intelligence governance: A review and research framework.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Responsible artificial intelligence governance: A review and research framework

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.940441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:30b3a9731dc0c77acea67c748b1fbabaaf73711912852cf73fa921f85d11f1b6

Observation 309eb63d-274c-4bb3-8d96-8504b8416570 · outbound

This paper cites Digital payments and GDP growth: A behavioural quantitative analysis.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Digital payments and GDP growth: A behavioural quantitative analysis

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.932639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:09a902f157eee702da101ca823852f75a07feff49deed3ac30d8d63d11925745

Observation b611f705-04cf-4a45-af12-11a688c6e33d · outbound

This paper cites India’s UPI revolution: over 18 billion transactions every month, a global leader in fast payments.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments India’s UPI revolution: over 18 billion transactions every month, a global leader in fast payments

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.944021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:49f39ec73e29cc4f774f59f6d602be39b4d259924ee92da4bd10328746ff142f

Observation 7d9f966f-db5e-477e-bfdc-64e97e1d558c · outbound

This paper cites The Challenges of Evaluating LLM Applications: An Analysis of Automated, Human, and LLM-Based Approaches.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments The Challenges of Evaluating LLM Applications: An Analysis of Automated, Human, and LLM-Based Approaches

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-18T20:36:50.281139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:6abbe48afc2fa79931f294cb2d354ae419b24b015f022e6cb1ee13f82512df2e

Observation f2e989b6-7eec-4170-b851-24f74bb1ea0d · outbound

This paper cites A comprehensive survey of cybercrimes in India over the last decade.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments A comprehensive survey of cybercrimes in India over the last decade

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.951714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:d8a0c7ba72f8fbb065f9e38d4fc7658cfde1dab3e77d4b141436f7de2b653cae

Observation b65ec573-dbd1-47c3-8e3c-633ef6f79303 · outbound

This paper cites Scams and frauds in the digital age: ML-based detection and prevention strategies.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Scams and frauds in the digital age: ML-based detection and prevention strategies

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.955379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:8a26e85681cb8317652edff77dbc0fba6a3b37a16a6d160e99743897a11e6a73

Observation dda28912-3d8b-442c-8b9d-cd87f2711716 · outbound

This paper cites An overview of 7726 user reports: uncovering sms scams and scammer strategies.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments An overview of 7726 user reports: uncovering sms scams and scammer strategies

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-18T20:36:50.275842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:50aed8cd36f4fa09ac90f2e4225086668342b946aab7669dc558ddab879d5aa0

Observation 570d9651-5773-41e8-a42b-87fa000b84f9 · outbound

This paper cites Combating investment scams: insights from law enforcement and civil society toward a prevention framework.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Combating investment scams: insights from law enforcement and civil society toward a prevention framework

Reference 20

Resolution
malformed identifier
doi_truncated, observed 2026-05-18T20:36:50.054999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:0a47d79f50af4689d4e4fbf77d6d31aab221118da150c26d8ad0b2bb6058bc26

Observation f12e444c-3b9d-4bbc-a269-5cbbcc80118a · outbound

This paper cites Chatbots in customer service within banking and finance: Do chatbots herald the start of an AI revolution in the corporate world?.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Chatbots in customer service within banking and finance: Do chatbots herald the start of an AI revolution in the corporate world?

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T20:36:50.958818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:ecaf4f421464964d5909ce94a04bb80a238b812902831e92809f6cfcb358f9bf

Observation a7408a69-4079-42ad-8eb2-4efaa90f97ef · outbound

This paper cites Decoding User Concerns in AI Health Chatbots: An Exploration of Security and Privacy in App Reviews.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Decoding User Concerns in AI Health Chatbots: An Exploration of Security and Privacy in App Reviews

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-18T20:36:50.254456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:4f11f902db8113aadd381a3cd1737b2bf03dca23ad25584d5c8b974521cd6041

Observation 96aaa4ce-4a31-457c-8c6c-fd4d26cb706f · outbound

This paper cites Enhancing trust and safety in digital pay- ments: an LLM-powered approach.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Enhancing trust and safety in digital pay- ments: an LLM-powered approach

Reference 23

Resolution
malformed identifier
doi_truncated, observed 2026-05-18T20:36:50.050172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:77e89cddfa897e84508a09937b3f49b4ae283bffcdcd1ccc64b13f5edc7f914f

Observation c6507f8a-1321-4c89-92b0-6ecfde8dd3f5 · outbound

This paper cites Large Language Models for Generative Information Extraction: A Survey.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Large Language Models for Generative Information Extraction: A Survey

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-18T20:36:50.261144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T20:35:29.338034Z digest=sha256:19258b5fe8def79e5491c769a8211c4276b0a82b1fa31495e1d73e0cb971631f

Pith citing papers

Observation 2659058c-315c-4d41-b22d-348feaef5486 · inbound

ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage cites this paper.

ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-05-20T22:33:48.599769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T22:31:48.012441Z digest=sha256:f5e94133be76fdd234d734ed5cda1264ebbf5b640bbf40b1a66c4ac53270aff6

Observation e2777191-b6e2-40aa-a1f6-ef7c773a282d · inbound

Operational Evidence Gaps for LLMs in Fraud Detection and Trust-and-Safety Workflows cites this paper.

Operational Evidence Gaps for LLMs in Fraud Detection and Trust-and-Safety Workflows CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-02T07:06:18.728116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:06:18.728116Z digest=sha256:15068650848d527e97bf16c50301276596a2f22481f637606fa666d8b1ce36d5