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Paper Citation Record · LEDGER

Understanding the Supply Chain and Risks of Large Language Model Applications

As of 19 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 3 inbound Pith citation observations for arXiv:2507.18105.

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

pith.paper-citation-record.v1
2507.18105 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:45:42.918332Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T18:19:22.704957Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T11:23:20.652907Z

Reference resolution

28 of 28 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved23
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 478c0260-db5f-4dfc-98f8-1b63e97a3c3e · outbound

This paper cites GPT in Sheep's Clothing: The Risk of Customized GPTs.

Understanding the Supply Chain and Risks of Large Language Model Applications GPT in Sheep's Clothing: The Risk of Customized GPTs

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:45:42.843682Z digest=sha256:85fbc34b507abd6017880e04de9d1cc9d99dd2d7730f955ae7b9e9c084e2b720

Observation d3ba34f9-1c35-4e95-95e9-11a2a237e2f3 · outbound

This paper cites Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems.

Understanding the Supply Chain and Risks of Large Language Model Applications Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems

Reference 5

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source=pdf_text observed=2026-08-06T14:45:42.856490Z digest=sha256:c8c408ab13352f77e6869729a9514f083a89e26f2233b1bc05d193692a1cea41

Observation c77d8cef-02d0-4b75-9aa2-e5755e690b87 · outbound

This paper cites Do Membership Inference Attacks Work on Large Language Models?.

Understanding the Supply Chain and Risks of Large Language Model Applications Do Membership Inference Attacks Work on Large Language Models?

Reference 6

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source=pdf_text observed=2026-08-06T14:45:42.859273Z digest=sha256:66b50d8df5376678441a98449fcef0919b8788f62a3bc3a298ca880479f6ada5

Observation f76eb40a-1cfc-4eb3-a032-1c0f60d1684f · outbound

This paper cites Euronews.

Understanding the Supply Chain and Risks of Large Language Model Applications Euronews

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:45:43.349486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T14:45:42.862277Z digest=sha256:00da4c84ad7bbd845b793bf9a933b200ff150578d90c12993143f57f05348f00

Observation 68928b11-7ff6-4c42-83df-f32e15bfefe5 · outbound

This paper cites RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models.

Understanding the Supply Chain and Risks of Large Language Model Applications RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models

Reference 8

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source=pdf_text observed=2026-08-06T14:45:42.864839Z digest=sha256:239cb468bab68879cca5dae73c69a67c3b514bf3528f1002329d8e69b761e2b6

Observation 2d33092b-5102-4e71-8f90-9b78061fb2d9 · outbound

This paper cites Membership Inference Attacks Against Vision-Language Models.

Understanding the Supply Chain and Risks of Large Language Model Applications Membership Inference Attacks Against Vision-Language Models

Reference 9

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source=pdf_text observed=2026-08-06T14:45:42.867566Z digest=sha256:c3a8204419ad184650e3eaef1143872d528db7d9faf0458ff3862012ae62af9e

Observation 79abd22c-240f-4b88-9725-857d62440946 · outbound

This paper cites Pleak: Prompt leaking attacks against large language model applications.

Understanding the Supply Chain and Risks of Large Language Model Applications Pleak: Prompt leaking attacks against large language model applications

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-06T14:45:43.341493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T14:45:42.870578Z digest=sha256:7921f77435cd260582678673a3ab2f361e7f3870b7251a5745d35a520700ee3b

Observation 45f7d85a-76f8-497c-aeac-667ff1e2f1cb · outbound

This paper cites Automatic and Universal Prompt Injection Attacks against Large Language Models.

Understanding the Supply Chain and Risks of Large Language Model Applications Automatic and Universal Prompt Injection Attacks against Large Language Models

Reference 11

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source=pdf_text observed=2026-08-06T14:45:42.873238Z digest=sha256:deb0815698af225cd94424d180179d8e432e69d40819625e3c8c627c5caab077

Observation fd7992d7-efc6-4419-a639-6b4406f9fa3b · outbound

This paper cites Prompt injection attacks and defenses in llm-integrated applications.

Understanding the Supply Chain and Risks of Large Language Model Applications Prompt injection attacks and defenses in llm-integrated applications

Reference 12

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no resolver link, observed 2026-08-06T14:45:42.875860Z

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source=pdf_text observed=2026-08-06T14:45:42.875860Z digest=sha256:cceb80725137211099181728e7137a7f2ce22e3c0da11aad52c7d46d44983757

Observation 195e5e04-dd03-4d1e-954b-35f46fa17331 · outbound

This paper cites Hallucination Detection and Hallucination Mitigation: An Investigation.

Understanding the Supply Chain and Risks of Large Language Model Applications Hallucination Detection and Hallucination Mitigation: An Investigation

Reference 13

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source=pdf_text observed=2026-08-06T14:45:42.878521Z digest=sha256:a77afe3e5331d05178809bc2fab46ecc1f868bf0c75e20c3ebd936d965d21c72

Observation 073fbee0-bcc0-4e77-b21a-12bce1fe1be1 · outbound

This paper cites optimum habana.

Understanding the Supply Chain and Risks of Large Language Model Applications optimum habana

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-06T14:45:43.331799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T14:45:42.881063Z digest=sha256:57f89c6fc2dccd2d9511a05cfe9bf0b0d047e4e3446c758d7f20231478121e8c

Observation 6351fe2a-e6e3-4c08-a69a-59f01f6f8c61 · outbound

This paper cites Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks.

Understanding the Supply Chain and Risks of Large Language Model Applications Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 17

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source=pdf_text observed=2026-08-06T14:45:42.889327Z digest=sha256:fc63fa16e2a35bb631712f476a78a77f8de0fa24ff19a30f018b315d7cc7897b

Observation a8275d30-351c-4cbc-8bb0-b15b933d8848 · outbound

This paper cites do anything now.

Understanding the Supply Chain and Risks of Large Language Model Applications do anything now

Reference 18

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source=pdf_text observed=2026-08-06T14:45:42.892043Z digest=sha256:9757d9ca267089c5098d6e5f524809f53ee45c7aa12d5b0f60f7eb91b9240c0a

Observation 26be40f3-5415-425a-8219-250a4daee581 · outbound

This paper cites The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence.

Understanding the Supply Chain and Risks of Large Language Model Applications The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence

Reference 19

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no resolver link, observed 2026-08-06T14:45:42.894869Z

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source=pdf_text observed=2026-08-06T14:45:42.894869Z digest=sha256:a4bdca1f734998bd2b66cc7a607a6ca9ffaafd4595e8ae23c52a40d29acb6a0b

Observation 13375ff6-15fa-4a4b-ba95-5de4e47f2642 · outbound

This paper cites Beyond Memorization: Violating Privacy Via Inference with Large Language Models.

Understanding the Supply Chain and Risks of Large Language Model Applications Beyond Memorization: Violating Privacy Via Inference with Large Language Models

Reference 20

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source=pdf_text observed=2026-08-06T14:45:42.897645Z digest=sha256:89eaa9fcf7874150cfac45dfc90b9e6722d6414791ef2699e06e7e1553fbc967

Observation de40687f-37e7-4e1d-91f2-504f0ef50e1c · outbound

This paper cites GPT Store Mining and Analysis.

Understanding the Supply Chain and Risks of Large Language Model Applications GPT Store Mining and Analysis

Reference 21

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source=pdf_text observed=2026-08-06T14:45:42.900068Z digest=sha256:7d4deb2d3acd26ee82b98d70311f61bff513f16f8d6deeae40525553be02af92

Observation 6de75f07-8ecc-469b-a13f-f5682673574a · outbound

This paper cites Opening A Pandora's Box: Things You Should Know in the Era of Custom GPTs.

Understanding the Supply Chain and Risks of Large Language Model Applications Opening A Pandora's Box: Things You Should Know in the Era of Custom GPTs

Reference 22

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source=pdf_text observed=2026-08-06T14:45:42.902778Z digest=sha256:245e793388ccb4bdac89465d75dfae6132ee7fdaed078fe2c555788c98168d85

Observation 11cb1854-b4d5-43b9-a785-e7a5328efa16 · outbound

This paper cites Demystifying LLM Supply Chain Vulnerabilities in the Wild: Distribution, Root Cause, and Real-World Impact.

Understanding the Supply Chain and Risks of Large Language Model Applications Demystifying LLM Supply Chain Vulnerabilities in the Wild: Distribution, Root Cause, and Real-World Impact

Reference 23

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source=pdf_text observed=2026-08-06T14:45:42.905342Z digest=sha256:6a7ad8a07082fe799381b993f2719f3200c55ee3cc3db07efebe476eadf05459

Observation 59a94714-65be-4576-ba57-7918469c847a · outbound

This paper cites A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems.

Understanding the Supply Chain and Risks of Large Language Model Applications A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems

Reference 24

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source=pdf_text observed=2026-08-06T14:45:42.907822Z digest=sha256:ad924a139a5b9462b5700666acf131ba4bf73a169b36f4c0e483343e2af9ea7b

Observation 28a72206-9954-4a91-87e2-f7ae87ed7169 · outbound

This paper cites LLM App Squatting and Cloning.

Understanding the Supply Chain and Risks of Large Language Model Applications LLM App Squatting and Cloning

Reference 25

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local_arxiv, observed 2026-08-06T14:45:42.973877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T14:45:42.910316Z digest=sha256:c8bd8ac6f29826c5611f3f534a2e2888f59b30973285fd92c46fb145bd0d4243

Observation c3576dbb-ce6f-4b77-ad91-e23a35fc89f5 · outbound

This paper cites A Comprehensive Study of Jailbreak Attack versus Defense for Large Language Models.

Understanding the Supply Chain and Risks of Large Language Model Applications A Comprehensive Study of Jailbreak Attack versus Defense for Large Language Models

Reference 26

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source=pdf_text observed=2026-08-06T14:45:42.912963Z digest=sha256:1a511e756341ffd567cb68102dda1e496ba2e06bd9c782d404a1214c3226f32c

Observation f9cfa140-0e73-4539-a549-803c09b61a3a · outbound

This paper cites GPTs Window Shopping: An analysis of the Landscape of Custom ChatGPT Models.

Understanding the Supply Chain and Risks of Large Language Model Applications GPTs Window Shopping: An analysis of the Landscape of Custom ChatGPT Models

Reference 27

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source=pdf_text observed=2026-08-06T14:45:42.915704Z digest=sha256:7524845b076509646f8f785f910ff622ee8de0659432adf32ee73984a92b1a80

Observation 44dd8d47-a542-4d88-b2d7-e04cd9399c11 · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Understanding the Supply Chain and Risks of Large Language Model Applications Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 28

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source=pdf_text observed=2026-08-06T14:45:42.918332Z digest=sha256:a873253494d1ebc5db24eedad761f54a55129148c3649cd79bc35f3706ca15b4

Observation 6a03dbd6-25ed-4eb4-aa92-813f9b93dba8 · outbound

This paper cites Rodrigo Pedro, Daniel Castro, Paulo Carreira, and Nuno Santos.

Understanding the Supply Chain and Risks of Large Language Model Applications Rodrigo Pedro, Daniel Castro, Paulo Carreira, and Nuno Santos

Reference 2020

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no resolver link, observed 2026-08-06T14:45:42.883615Z

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source=pdf_text observed=2026-08-06T14:45:42.883615Z digest=sha256:595d7b4c38776682837002c353a3e25cf30c96a39544d3190af5b63319a6f915

Observation 0c92356b-90be-4aa5-9449-ebcfa0883c74 · outbound

This paper cites Are LLMs Correctly Integrated into Software Systems?.

Understanding the Supply Chain and Risks of Large Language Model Applications Are LLMs Correctly Integrated into Software Systems?

Reference 2022

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no resolver link, observed 2026-08-06T14:45:42.886374Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:45:42.886374Z digest=sha256:bba5dea57f680922dd0a80db6ff6d64b69f2f1e268bb323c31ea2d007c9eeeff

Observation d774bde4-04ad-4642-a39d-027538703ada · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Understanding the Supply Chain and Risks of Large Language Model Applications On the Opportunities and Risks of Foundation Models

Reference 2023

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source=pdf_text observed=2026-08-06T14:45:42.850187Z digest=sha256:6a2d691dbc716846090fe93c5a5a98b6c6dc1fc075ecab3550fa860038265823

Observation 97794215-ada6-49f4-9f3e-40a02bb0b665 · outbound

This paper cites Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models.

Understanding the Supply Chain and Risks of Large Language Model Applications Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models

Reference 2024

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source=pdf_text observed=2026-08-06T14:45:42.847281Z digest=sha256:b2469655b1e8a2a75fcee17b3f3cc22aa6906baaf0b4f34a49ca219353df161e

Observation f9454b0b-8c8d-44ad-898e-cd51dce5e8ea · outbound

This paper cites Are aligned neural networks adversarially aligned?.

Understanding the Supply Chain and Risks of Large Language Model Applications Are aligned neural networks adversarially aligned?

Reference 2025

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source=pdf_text observed=2026-08-06T14:45:42.853648Z digest=sha256:e5b78e51310f559444941a93d4a008b7dc0cd9c1121e7653678404b0a8fdd0d1

Pith citing papers

Observation 1e4dfd33-50d3-43b1-b342-a838ca8a1474 · inbound

LLM Harms: A Taxonomy and Discussion cites this paper.

LLM Harms: A Taxonomy and Discussion Understanding the Supply Chain and Risks of Large Language Model Applications

Reference 135

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verified exact
arxiv_id, observed 2026-05-17T00:31:24.848266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-17T00:29:07.951709Z digest=sha256:3c9b834dabc6c1b5b0486eaec4c0225e0535ba392c8ae6e3a7c9693bb3e8f58c

Observation 7a949494-50f9-474c-bd0a-0298e0d2d958 · inbound

LLM Harms: A Taxonomy and Discussion cites this paper.

LLM Harms: A Taxonomy and Discussion Understanding the Supply Chain and Risks of Large Language Model Applications

Reference 135

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source=pdf_text observed=2026-08-03T18:19:22.704957Z digest=sha256:400d6dccc62fbc360aaaae1a1afe4e08b7db4753420b3728a1829244cf058a68

Observation e801676c-16a2-4b64-b0e4-7877a013223a · inbound

Towards Demystifying and Repairing LLM-in-the-Loop Vulnerabilities cites this paper.

Towards Demystifying and Repairing LLM-in-the-Loop Vulnerabilities Understanding the Supply Chain and Risks of Large Language Model Applications

Reference 31

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arxiv_id, observed 2026-06-29T11:23:20.654722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-29T11:21:33.012202Z digest=sha256:42a3ce000d8e53ef20b16337438218ba0b895b69f8f9a98c9b6bf7c7e6d92fba