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Paper Citation Record · LEDGER

Governable AI: Provable Safety Under Extreme Threat Models

As of 9 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2508.20411.

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

pith.paper-citation-record.v1
2508.20411 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:11:19.776229Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

50 of 50 outbound references displayed

  • verified exact2
  • verified fuzzy46
  • unresolved2
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 27931313-5828-4758-8e5a-3db9dee343ed · outbound

This paper cites An overview of artificial intelligence ethics,.

Governable AI: Provable Safety Under Extreme Threat Models An overview of artificial intelligence ethics,

Reference 1

Resolution
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Observation c343b529-90ad-48ea-bfd3-333b34af09f7 · outbound

This paper cites Language models are few-shot learn- ers,.

Governable AI: Provable Safety Under Extreme Threat Models Language models are few-shot learn- ers,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 245f2eb2-d7ef-42c7-9dfe-2e3a3a8541c5 · outbound

This paper cites Supervised contrastive learning for generalizable and explainable deepfakes detec- tion,.

Governable AI: Provable Safety Under Extreme Threat Models Supervised contrastive learning for generalizable and explainable deepfakes detec- tion,

Reference 3

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 4d027ea3-a53a-4228-bd43-57687e9b7912 · outbound

This paper cites Artificial super intelligence: beyond rhetoric,.

Governable AI: Provable Safety Under Extreme Threat Models Artificial super intelligence: beyond rhetoric,

Reference 4

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 51aec41b-69e2-4bf9-ac6a-50ffad4934fc · outbound

This paper cites Ai safety for everyone,.

Governable AI: Provable Safety Under Extreme Threat Models Ai safety for everyone,

Reference 5

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 186065f3-5a9a-4f19-b83f-01110e2bca8f · outbound

This paper cites Actionable Guidance for High-Consequence AI Risk Management: Towards Standards Addressing AI Catastrophic Risks.

Governable AI: Provable Safety Under Extreme Threat Models Actionable Guidance for High-Consequence AI Risk Management: Towards Standards Addressing AI Catastrophic Risks

Reference 6

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Observation b4d3f359-83d6-431a-9531-ce675fd325e6 · outbound

This paper cites Learning diverse and discriminative representations via the principle of maximal coding rate reduction,.

Governable AI: Provable Safety Under Extreme Threat Models Learning diverse and discriminative representations via the principle of maximal coding rate reduction,

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 41d5b5cc-b15d-47aa-bf03-34bc14d561f5 · outbound

This paper cites A dempster-shafer ap- proach to trustworthy ai with application to fetal brain mri segmentation,.

Governable AI: Provable Safety Under Extreme Threat Models A dempster-shafer ap- proach to trustworthy ai with application to fetal brain mri segmentation,

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation be77dc22-2eb2-4e2a-9210-6c78ae6c0850 · outbound

This paper cites Vistarag: Toward safe and trustworthy autonomous driving through retrieval- augmented generation,.

Governable AI: Provable Safety Under Extreme Threat Models Vistarag: Toward safe and trustworthy autonomous driving through retrieval- augmented generation,

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 31022221-06ad-4a3c-8236-0fdfeda5acff · outbound

This paper cites AI Alignment: A Comprehensive Survey.

Governable AI: Provable Safety Under Extreme Threat Models AI Alignment: A Comprehensive Survey

Reference 10

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Source-reported events for the cited work

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Observation 5616076c-50d1-4de6-9fd1-a266e364d78d · outbound

This paper cites How rl agents behave when their actions are modified,.

Governable AI: Provable Safety Under Extreme Threat Models How rl agents behave when their actions are modified,

Reference 11

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9fcb0099-3311-4104-bc9f-aa74215d568f · outbound

This paper cites Alignment of Language Agents.

Governable AI: Provable Safety Under Extreme Threat Models Alignment of Language Agents

Reference 12

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6173e3bc-341d-4c54-a222-62cafca2f1c9 · outbound

This paper cites On controllability of artificial intelli- gence,.

Governable AI: Provable Safety Under Extreme Threat Models On controllability of artificial intelli- gence,

Reference 13

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9cf1ff90-c22e-4086-8487-d93324efcf73 · outbound

This paper cites You should not control what you do not understand: the risks of controllability in ai,.

Governable AI: Provable Safety Under Extreme Threat Models You should not control what you do not understand: the risks of controllability in ai,

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 083749dd-8530-4def-b6b9-6a445b8f0636 · outbound

This paper cites Rethinking explainable ai in financial services,.

Governable AI: Provable Safety Under Extreme Threat Models Rethinking explainable ai in financial services,

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation fb77d667-5abf-4eca-a1a4-e01eab9cb631 · outbound

This paper cites A review on explainable artificial intelligence for healthcare: Why, how, and when?.

Governable AI: Provable Safety Under Extreme Threat Models A review on explainable artificial intelligence for healthcare: Why, how, and when?

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e7a27ea5-c8a5-4aa0-b5c3-b7beebf08309 · outbound

This paper cites A counterintuitive approach to explainable ai in healthcare: balancing transparency, efficiency, and cost,.

Governable AI: Provable Safety Under Extreme Threat Models A counterintuitive approach to explainable ai in healthcare: balancing transparency, efficiency, and cost,

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 35f4fdf1-174e-4716-86bb-3019a55be066 · outbound

This paper cites Jcs: An explainable covid-19 diagnosis system by joint classification and segmentation,.

Governable AI: Provable Safety Under Extreme Threat Models Jcs: An explainable covid-19 diagnosis system by joint classification and segmentation,

Reference 18

Resolution
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8728d111-8a00-4a6c-ac3a-5cc1334245b6 · outbound

This paper cites Xaitk-saliency: An open source explainable ai toolkit for saliency,.

Governable AI: Provable Safety Under Extreme Threat Models Xaitk-saliency: An open source explainable ai toolkit for saliency,

Reference 19

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 65d0da57-b416-44dd-9cb6-116269c09bce · outbound

This paper cites Neuro-symbolic explainable artificial intelligence twin for zero-touch ioe in wireless network,.

Governable AI: Provable Safety Under Extreme Threat Models Neuro-symbolic explainable artificial intelligence twin for zero-touch ioe in wireless network,

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 34899692-4018-493a-b557-4fedd855a3da · outbound

This paper cites Advanced artificial agents intervene in the provision of reward,.

Governable AI: Provable Safety Under Extreme Threat Models Advanced artificial agents intervene in the provision of reward,

Reference 21

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0706575c-38c3-40a9-a1af-96ef472d0817 · outbound

This paper cites Controllable ai-an alternative to trustworthiness in complex ai systems?.

Governable AI: Provable Safety Under Extreme Threat Models Controllable ai-an alternative to trustworthiness in complex ai systems?

Reference 22

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0b4bc069-242a-4392-a40f-d6242f887657 · outbound

This paper cites Resource allocation and trust computing for blockchain- enabled edge computing system,.

Governable AI: Provable Safety Under Extreme Threat Models Resource allocation and trust computing for blockchain- enabled edge computing system,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 4253ce1b-3495-4680-939f-850e4209890c · outbound

This paper cites Design and implementation of trusted boot based on a new trusted computing dual- architecture,.

Governable AI: Provable Safety Under Extreme Threat Models Design and implementation of trusted boot based on a new trusted computing dual- architecture,

Reference 24

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation cf528b45-ead5-4adc-8d25-9846cd0c9383 · outbound

This paper cites Trusted platform module,.

Governable AI: Provable Safety Under Extreme Threat Models Trusted platform module,

Reference 25

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 506605f3-ea30-4d3f-a50b-0c3b3a713735 · outbound

This paper cites Research on trusted com- puting and its development,.

Governable AI: Provable Safety Under Extreme Threat Models Research on trusted com- puting and its development,

Reference 26

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 3c1e2176-0efa-4c6d-a935-e799e7e8da8d · outbound

This paper cites An extensive investigation of condition reachability using cbmc: Study on negative results,.

Governable AI: Provable Safety Under Extreme Threat Models An extensive investigation of condition reachability using cbmc: Study on negative results,

Reference 27

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 99942227-0eba-4354-a319-bd14e3a6714b · outbound

This paper cites Klee symbolic execution engine in 2019,.

Governable AI: Provable Safety Under Extreme Threat Models Klee symbolic execution engine in 2019,

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0f685f83-35aa-478f-8744-3e66f760f06e · outbound

This paper cites A formalization of core why3 in coq,.

Governable AI: Provable Safety Under Extreme Threat Models A formalization of core why3 in coq,

Reference 29

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 3d81a7de-3df3-467c-90e0-250e4d0aed2e · outbound

This paper cites Isarare: automatic verification of smt rewrites in isabelle/hol,.

Governable AI: Provable Safety Under Extreme Threat Models Isarare: automatic verification of smt rewrites in isabelle/hol,

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e7db28c5-8495-4308-9a6c-8a9839f278ca · outbound

This paper cites Application of formal methods (sat/smt) to the design of constrained codes,.

Governable AI: Provable Safety Under Extreme Threat Models Application of formal methods (sat/smt) to the design of constrained codes,

Reference 31

Resolution
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raw_fallback, observed 2026-08-05T15:11:22.417286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9d8f77d7-2597-44b1-8310-0e745981ab2d · outbound

This paper cites Clips user’s guide,.

Governable AI: Provable Safety Under Extreme Threat Models Clips user’s guide,

Reference 32

Resolution
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raw_fallback, observed 2026-08-05T15:11:22.181561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 93655ad7-bdf1-49c1-98bc-7ecb9edd55fd · outbound

This paper cites Bali, Drools JBoss rules 5.0 developer’s guide.

Governable AI: Provable Safety Under Extreme Threat Models Bali, Drools JBoss rules 5.0 developer’s guide

Reference 33

Resolution
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raw_fallback, observed 2026-08-05T15:11:21.939719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e589c810-e0c4-4ef3-9ad8-7301aa57e39f · outbound

This paper cites Friedman-Hill, Jess in action: rule-based systems in Java.

Governable AI: Provable Safety Under Extreme Threat Models Friedman-Hill, Jess in action: rule-based systems in Java

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:21.634746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.424158Z digest=sha256:e1596962a90a5375fcc36b8e46d66ce347d02aaaa5679ab5cb1508473b26e600

Observation b14242d4-6423-44cc-b266-e57c4b708001 · outbound

This paper cites Fifty years of prolog and beyond,.

Governable AI: Provable Safety Under Extreme Threat Models Fifty years of prolog and beyond,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:21.541960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.441728Z digest=sha256:eb91d0d4c0349699c6fc09a47edcdff0efc7b8118ef305c24c401586f6c65303

Observation 699e33f6-2c74-4368-b748-45559b2e443a · outbound

This paper cites Openssl 3.0. 0: An exploratory case study,.

Governable AI: Provable Safety Under Extreme Threat Models Openssl 3.0. 0: An exploratory case study,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:21.458102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.449450Z digest=sha256:56946ff85b1375954fc3b15bf79bde36cbef99e150881188066bfee7edcff8bc

Observation a0c5a94b-d905-428d-929a-fe75f9fcebb4 · outbound

This paper cites Information security using gnu privacy guard,.

Governable AI: Provable Safety Under Extreme Threat Models Information security using gnu privacy guard,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:21.397762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.462725Z digest=sha256:7f6998856a26c9e0b1765fd370ab96cbe720b351451f796ef958af9aa99d0511

Observation a7cafd03-5022-4e39-be7d-33134a519bb1 · outbound

This paper cites Sigstore: Software signing for everybody,.

Governable AI: Provable Safety Under Extreme Threat Models Sigstore: Software signing for everybody,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:21.342948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.475397Z digest=sha256:01c3f09554e23d95193a9ce472caf5eec2808963b0389d9c4a54bede9dee4a5e

Observation c41d2825-89c1-4408-8250-f8e3b079a11c · outbound

This paper cites The broken verifying: Inspections at verification tools for windows code-signing signatures,.

Governable AI: Provable Safety Under Extreme Threat Models The broken verifying: Inspections at verification tools for windows code-signing signatures,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:21.305011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.502502Z digest=sha256:f9d73b089d260de67998b5c0d68021fc3e938219886aa46eb641dca9fbb1b89a

Observation b0ea8480-a35d-4c7a-8951-8e0860a41894 · outbound

This paper cites The provable security of ed25519: theory and practice,.

Governable AI: Provable Safety Under Extreme Threat Models The provable security of ed25519: theory and practice,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:21.228581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.544750Z digest=sha256:200314d308e22bfe447b73d987b81fd3b411e2003c15ad14877706be39f3da02

Observation fd31b93a-7e60-41c6-ac9e-7db7e71e9b4b · outbound

This paper cites Performance analysis of kyber-dna and rsa-base64 algorithms in symmetric key- exchange protocol,.

Governable AI: Provable Safety Under Extreme Threat Models Performance analysis of kyber-dna and rsa-base64 algorithms in symmetric key- exchange protocol,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:21.176335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.584739Z digest=sha256:08a71bb04667121759ea435f08291a892138ba5c6a62355fb2bd899dc352595b

Observation 1264fc34-4fb1-4b5e-9939-2947274ec2cd · outbound

This paper cites Fast two-party threshold ecdsa with proactive security,.

Governable AI: Provable Safety Under Extreme Threat Models Fast two-party threshold ecdsa with proactive security,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:21.113505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.621662Z digest=sha256:c564e7e312ee7ed48d5d09c7bca2cb00cc491cd55f77762e8d3c1f33a6cc106f

Observation 2e2938e4-21ad-4ffb-9941-b335c0c3385a · outbound

This paper cites High-speed high-security signatures,.

Governable AI: Provable Safety Under Extreme Threat Models High-speed high-security signatures,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:20.995969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.637359Z digest=sha256:dcf7432add6a659610de503cefe03fa302e08cbd4b9a15e6bb05f5162b8b1e88

Observation 657574a5-ee48-4998-a3c4-139292694ab3 · outbound

This paper cites Nist special publication 800-57 part 1, revision 4,.

Governable AI: Provable Safety Under Extreme Threat Models Nist special publication 800-57 part 1, revision 4,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:20.924743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.674747Z digest=sha256:2b7556281da970a6e77f0b90747e97777f028f7dac3cd560c62e3480e193e1ad

Observation 7c6a14fd-c61b-4170-a680-ac834b716e7a · outbound

This paper cites Post-quantum cryptography for linux file system integrity,.

Governable AI: Provable Safety Under Extreme Threat Models Post-quantum cryptography for linux file system integrity,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:20.814757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.684767Z digest=sha256:b16232b8457e9cc027f18518f28d7d4d63027b15ab1d4d072b22e4ba6e7633b3

Observation db70bf33-db52-40b8-98c3-2a2e42b9ecea · outbound

This paper cites On the security of pkcs# 11,.

Governable AI: Provable Safety Under Extreme Threat Models On the security of pkcs# 11,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:20.644049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.714830Z digest=sha256:191c3bf04ba6b79ac4598170b939c260fa084b32cb9643b6cb55585c03950ffa

Observation f256452b-e955-48c7-bdf4-69f88055f651 · outbound

This paper cites Enhanced memory- safe linux security modules (elsms) for improving security of docker containers for data centers,.

Governable AI: Provable Safety Under Extreme Threat Models Enhanced memory- safe linux security modules (elsms) for improving security of docker containers for data centers,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:20.554747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.722450Z digest=sha256:56a0e001355656bca0b2eb5a663c2cb0bb155417ff855ba936a7d49af19defa1

Observation 2bf7b5ef-41f4-40f1-91fb-3ebbe9a6c7f1 · outbound

This paper cites Apparmor technical doc- umentation,.

Governable AI: Provable Safety Under Extreme Threat Models Apparmor technical doc- umentation,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:20.511496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.755828Z digest=sha256:594133e1c05b8e2a7bd27c5c744eec181e11f82e442562d84b74536e5ffe50bb

Observation 0c2c1cdf-9353-4922-b770-fd9d39be1721 · outbound

This paper cites Implementing selinux as a linux security module,.

Governable AI: Provable Safety Under Extreme Threat Models Implementing selinux as a linux security module,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:20.362456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.770646Z digest=sha256:357bec01bb21a966e9094d5f44a9571ef79dad03559dc2529aef28e0d36f6bb8

Observation dc548bdb-f4e5-40f0-8325-f9fa2e60bceb · outbound

This paper cites Au- tomating seccomp filter generation for linux applications,.

Governable AI: Provable Safety Under Extreme Threat Models Au- tomating seccomp filter generation for linux applications,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:11:20.214837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T15:11:19.776229Z digest=sha256:583dafa2075d33a891b325df01929b3744354b940a71f35eda9de8d6723f1810

Pith citing papers

No inbound Pith citation observations are available.