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Paper Citation Record · LEDGER

Adversarial Prompting Framework for AI Safety Assessment

As of 7 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 2026-08-07T06:34:17.273281+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.

source=pdf_text observed=2026-08-02T05:10:09.277660Z digest=sha256:3a0471e6ccf97f84324a48603e6ea57ba579297e16a7c3e5714d744c546a82d5

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.

source=pdf_text observed=2026-08-02T05:10:09.282584Z digest=sha256:6e1659955c84c680e55f6a37d391c60276c197d26f0929ccef22c577f57b4c0a

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.

source=pdf_text observed=2026-08-02T05:10:09.286112Z digest=sha256:d1e82e2e88660a0ff613d8a488b2de560399cf2b9d06c73d4c6589589a4da7a7

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.

source=pdf_text observed=2026-08-02T05:10:09.289891Z digest=sha256:26399f457c98317774730b3729f8e84a3a035d3082da96decb798311d2d0f814

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.

source=pdf_text observed=2026-08-02T05:10:09.293937Z digest=sha256:c2ebebb9bfaade31ad4f3ea56158e83c35ac8594cc90d14d588b3022f9343694

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.

source=pdf_text observed=2026-08-02T05:10:09.301694Z digest=sha256:02a412621d81ea9a1a2d29a2daeae9c059745b26c231fd02478d5c26c523a9ad

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.

source=pdf_text observed=2026-08-02T05:10:09.305212Z digest=sha256:133f903630108b1a045d20b78bec44aaad6617c9d755263d5c09b9b9f0b07229

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.

source=pdf_text observed=2026-08-02T05:10:09.308254Z digest=sha256:e57c00a560d09fbeb708b501eb1fa421f06946f1393ba9c737b7c52e618a3418

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.

source=pdf_text observed=2026-08-02T05:10:09.311606Z digest=sha256:882242d75b31c5651c196095b1632c66b41f48118b2a678a4a5b2b2d1ecff805

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.

source=pdf_text observed=2026-08-02T05:10:09.315243Z digest=sha256:bac2ecdf8d4a0b9f16e1a0b79f89adf01f3afe3e2441b6269920f139fa374bfb

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.

source=pdf_text observed=2026-08-02T05:10:09.318644Z digest=sha256:50fd6633ed3093b5b4cf867d2fc27e98b61af9879e5d72c8c23cea7ddd6788ca

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.

source=pdf_text observed=2026-08-02T05:10:09.322238Z digest=sha256:c6a398d5c85792a21c02c0410c84fa734874802c2d5c6895d9ed6cbd7e1510e9

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.

source=pdf_text observed=2026-08-02T05:10:09.325522Z digest=sha256:34fafaf53c54c1e16adad7ca73ee9edf98a4f3c50fac13e3f84c971d2d00f4a9

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.

source=pdf_text observed=2026-08-02T05:10:09.331687Z digest=sha256:a78419d798af78af4b999a37bcdbe0f66b4bfe8a88ddf5de7249e547d3f77bf0

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.

source=pdf_text observed=2026-08-02T05:10:09.334593Z digest=sha256:81d7829fc32bf255cfb5f8ea6635bde495223f7ba5264b68dfe819a5e7265f79

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.

source=pdf_text observed=2026-08-02T05:10:09.337586Z digest=sha256:360049142cd204f7fea9d4532bf056e2b4bc76afdc450ff0005112ab805f49c8

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.

source=pdf_text observed=2026-08-02T05:10:09.340449Z digest=sha256:2b5dc9a6565ee6258b0285294cba767f99f11d4ebbfa45410f78c08a40e2c207

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.

source=pdf_text observed=2026-08-02T05:10:09.297490Z digest=sha256:1fbee60392ac017fbb766a2ec6fe1a9e7d4a286ff855edbd65190fe95bcb5257

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.

source=pdf_text observed=2026-08-02T05:10:09.328511Z digest=sha256:57f5369ef2665d2ae854a8d54595453364e7293a2c14c2806bcb7fc4b00a1fde

Pith citing papers

No inbound Pith citation observations are available.