Paper Citation Record · LEDGER

Adversarial Prompting Framework for AI Safety Assessment

As of 20 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2607.13453.

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

pith.paper-citation-record.v1
2607.13453 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T05:10:09.340449Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

19 of 19 outbound references displayed

verified exact0
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 48ab9af9-a1af-4b86-b4b7-8acda2639b5b · outbound

This paper cites Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices.

Adversarial Prompting Framework for AI Safety Assessment Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.277660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cd85fd1-62b0-499d-b90c-19066809408f · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.282584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f44c8d7d-7b31-4ed5-a9cb-48169d087401 · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.286112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecb94da7-7e5f-41c0-91a9-11c532e3b281 · outbound

This paper cites Design Patterns for Securing LLM Agents against Prompt Injections.

Adversarial Prompting Framework for AI Safety Assessment Design Patterns for Securing LLM Agents against Prompt Injections

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.289891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3087fec-bf9d-495c-bc44-68f1a470f1c3 · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.293937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56c455cd-9598-47e6-8b83-2e8b1ff33d18 · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.301694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ff704ea-e0a1-4ab6-b0ec-e3cabb6b10bf · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.305212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac89e6f3-54be-4555-84cf-4faf9daf2273 · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.308254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 326a7ec9-6175-4326-9895-1773e2c28488 · outbound

This paper cites SHADE-Arena: Evaluating Sabotage and Monitoring in LLM Agents.

Adversarial Prompting Framework for AI Safety Assessment SHADE-Arena: Evaluating Sabotage and Monitoring in LLM Agents

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.311606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f11db4e2-a816-4d47-aad9-ec665cf4ea53 · outbound

This paper cites Security Concerns for Large Language Models: A Survey.

Adversarial Prompting Framework for AI Safety Assessment Security Concerns for Large Language Models: A Survey

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.315243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 124d75ff-2ce3-4d90-8d3b-8f23d284d15a · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.318644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2aa7976-050a-4381-b1ae-729ea967f4fe · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.322238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6460a8f3-04f3-4312-833b-8db9d205019b · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.325522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e516e7ad-8b58-43a3-a27d-347eb0fe8b0f · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.331687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7109c620-3392-4cf0-86c5-2eb3c33216c7 · outbound

This paper cites Chi, Quoc V.

Adversarial Prompting Framework for AI Safety Assessment Chi, Quoc V

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.334593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebbce426-feef-4a93-b4fa-f4fd77db8c8e · outbound

This paper cites an unresolved cited work.

Adversarial Prompting Framework for AI Safety Assessment Unresolved cited work

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.337586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7080aee9-7160-4a9c-920e-005c1a249a15 · outbound

This paper cites Jailbreak Attacks and Defenses Against Large Language Models: A Survey.

Adversarial Prompting Framework for AI Safety Assessment Jailbreak Attacks and Defenses Against Large Language Models: A Survey

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.340449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3a8598d-64f3-4614-9be2-1868cfa147ed · outbound

This paper cites Recent Advances in Attack and Defense Approaches of Large Language Models.

Adversarial Prompting Framework for AI Safety Assessment Recent Advances in Attack and Defense Approaches of Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.297490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7269380-e39e-4834-892e-0b2b16f5866b · outbound

This paper cites https: //www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai.

Adversarial Prompting Framework for AI Safety Assessment https: //www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:09.328511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.