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Paper Citation Record · LEDGER

AI Safety in Generative AI Large Language Models: A Survey

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 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 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:21:39.609549Z

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-23T20:58:16.237327Z digest=sha256:56fc369db07122a61b97d45ff1a574eec40aff9bc4691424c64503c7295c4617

Observation c43d90d3-fa69-4567-b134-ac548c07ff3e · inbound

LLMs are Also Effective Embedding Models: An In-depth Overview cites this paper.

LLMs are Also Effective Embedding Models: An In-depth Overview AI Safety in Generative AI Large Language Models: A Survey

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T13:59:01.557315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:59:01.557315Z digest=sha256:c590837ac6920077351a872dca0ce95a1c1424483267838fbc3f1930164b8756

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.

source=pdf_text observed=2026-08-08T05:42:43.350763Z digest=sha256:3c5b6faa9fc18aea5e1b4b63f1f6ef5c912494078b03c0eeac47b5736ae83b80

Observation 57363400-a85a-4127-8497-fd062178bb27 · inbound

GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection cites this paper.

GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection AI Safety in Generative AI Large Language Models: A Survey

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T20:21:39.609549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:21:39.609549Z digest=sha256:fe81df57c5521ad3078cfb8b2a5f3470c582309bc94cb8ba73e1995a4d3303e9

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.

source=arxiv_source observed=2026-08-07T13:05:13.229440Z digest=sha256:b3e4102a3e64581367853817b11aaf528551afafa44ceaff43360cfdc1f80528

Observation 563b23b8-1ce6-4b94-9e17-4761aaa2d99a · inbound

Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects cites this paper.

Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects AI Safety in Generative AI Large Language Models: A Survey

Reference 154

Resolution
unresolved
no resolver link, observed 2026-08-15T19:20:30.004937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:20:30.004937Z digest=sha256:446d6ffebfff710555cc55a9b43aa21297e27e18e4c4ff42adc40de93fb160c8

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.

source=arxiv_source observed=2026-08-06T13:05:31.021856Z digest=sha256:7ecd7e253479c37ab074db916bf6eb1707c95f3328bc80ea9050a5973c3c99da

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.

source=pdf_text observed=2026-08-04T17:46:15.534041Z digest=sha256:fb0bb4b3230166a87f9af9feba4b234ad5eecff19521a25525d4f415378f5498

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-18T13:40:56.462752Z digest=sha256:60757a917fd75b4cc34a40fc3bc6778803c903d3917fa90e65c950d1cec82c09

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-25T07:02:03.058731Z digest=sha256:611dcd9ba404ef30222188cd9032ae92c82ab34616426cf28311813bb476dfd1

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-19T21:28:00.370745Z digest=sha256:3701a0c4937372f87064094bce3e041cd18c3aadadce8918abd29b37021a00ee

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.

source=pdf_text observed=2026-08-01T12:54:31.318319Z digest=sha256:83bdfbd21756d961d5abbf9123f1cc1b7632d2dff79570505d7b92d2059c8fe8