Paper Citation Record · LEDGER

AI Safety in Generative AI Large Language Models: A Survey

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2407.18369.

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

pith.paper-citation-record.v1
2407.18369 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:42:43.350763Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T07:05:26.705606Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation debd9f86-eca0-4293-9de9-14d9afd032ec · inbound

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey cites this paper.

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey AI Safety in Generative AI Large Language Models: A Survey

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:58:25.894483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f53513aa-31b3-4962-8c6c-b5e4dac5edd3 · inbound

Compromising Honesty and Harmlessness in Language Models via Deception Attacks cites this paper.

Compromising Honesty and Harmlessness in Language Models via Deception Attacks AI Safety in Generative AI Large Language Models: A Survey

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T05:42:43.350763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 353b90be-9473-48da-a2a8-d7f5709cbdb4 · inbound

Contextual Memory Intelligence -- A Foundational Paradigm for Human-AI Collaboration and Reflective Generative AI Systems cites this paper.

Contextual Memory Intelligence -- A Foundational Paradigm for Human-AI Collaboration and Reflective Generative AI Systems AI Safety in Generative AI Large Language Models: A Survey

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T13:05:13.229440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a903a97-b008-49c6-970b-5fad08a52fc0 · inbound

Agentic Web: Weaving the Next Web with AI Agents cites this paper.

Agentic Web: Weaving the Next Web with AI Agents AI Safety in Generative AI Large Language Models: A Survey

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T13:05:31.021856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e931669-dac3-4e82-930f-fb28b67352aa · inbound

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems cites this paper.

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems AI Safety in Generative AI Large Language Models: A Survey

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-04T17:46:15.534041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22579f6f-df6d-4e24-9170-2e773c0335f7 · inbound

Limitations on Accurate, Trusted, Human-level Reasoning cites this paper.

Limitations on Accurate, Trusted, Human-level Reasoning AI Safety in Generative AI Large Language Models: A Survey

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:41:25.416756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1becb8b7-776b-4d32-8d08-0bdc406c56d6 · inbound

BarrierSteer: LLM Safety via Learning Barrier Steering cites this paper.

BarrierSteer: LLM Safety via Learning Barrier Steering AI Safety in Generative AI Large Language Models: A Survey

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-25T07:05:26.708578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f1913cdc-300f-4110-9ecd-8bdfd474c4cb · inbound

State Contamination in Memory-Augmented LLM Agents cites this paper.

State Contamination in Memory-Augmented LLM Agents AI Safety in Generative AI Large Language Models: A Survey

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-19T21:32:48.050138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 95e47241-9ef1-41cd-9da4-6d8ac5062c71 · inbound

The safety failures we are not instrumenting: a perspective on hidden safety-critical challenges in modern AI systems cites this paper.

The safety failures we are not instrumenting: a perspective on hidden safety-critical challenges in modern AI systems AI Safety in Generative AI Large Language Models: A Survey

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T12:54:31.318319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.