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Paper Citation Record · LEDGER

SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2404.05399.

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

pith.paper-citation-record.v1
2404.05399 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:13:30.092281Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation df429bb7-57ef-4a1d-b322-874352820a3f · 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 SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 130

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:58:26.340665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-23T20:58:16.237327Z digest=sha256:4aaff64947bd0fdd8a2769b79e8d888fb6b5add8f2a83367b18137c9c5996993

Observation 954e25ab-33c8-4929-b8f1-380b590e7ecf · inbound

ChemSafetyBench: Benchmarking LLM Safety on Chemistry Domain cites this paper.

ChemSafetyBench: Benchmarking LLM Safety on Chemistry Domain SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T14:13:30.092281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:13:30.092281Z digest=sha256:c5e0aebaa4b77736a8a9b4e12451e254dfe9e3a2a497c66c0679ee09bf912a02

Observation bf269b6a-c25c-446e-9e89-097d08acb6a5 · inbound

Unanswerability Evaluation for Retrieval Augmented Generation cites this paper.

Unanswerability Evaluation for Retrieval Augmented Generation SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T14:17:45.650508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:17:45.650508Z digest=sha256:faa589d3745d0b48f1460ca16d76c84df8688112c7c68e0d541c65b62e41a468

Observation 8970fa6b-b913-4478-b857-ae4050d7978c · inbound

MSTS: A Multimodal Safety Test Suite for Vision-Language Models cites this paper.

MSTS: A Multimodal Safety Test Suite for Vision-Language Models SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:42.283054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:42.283054Z digest=sha256:13c61115927aeebe17f1ad8beb7a50d450ced14fd2d4c974e5d7d4650e6e2fdc

Observation d7740124-b0a3-43cf-a18a-6527eb78b1c4 · inbound

The Dual-use Dilemma in LLMs: Do Empowering Ethical Capacities Make a Degraded Utility? cites this paper.

The Dual-use Dilemma in LLMs: Do Empowering Ethical Capacities Make a Degraded Utility? SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T18:31:03.430895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:31:03.430895Z digest=sha256:1d9046575b4fd95f07fb2ddcd6063900c5bc223b85c6ab8fe762eccdc8c353df

Observation 6bf7b4fc-e841-49b8-82ea-7ebdab08f0f8 · inbound

Fairness through Difference Awareness: Measuring Desired Group Discrimination in LLMs cites this paper.

Fairness through Difference Awareness: Measuring Desired Group Discrimination in LLMs SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-09T14:03:44.571544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:03:44.571544Z digest=sha256:da8c6a3d16fe75519cf8ec6ff529a04dff81088a5690689d99c6724ce51a7d6d

Observation b9781829-87d8-42f1-86ca-70eb5debe28d · inbound

Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation cites this paper.

Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 110

Resolution
unresolved
no resolver link, observed 2026-08-08T15:06:55.258331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T15:06:55.258331Z digest=sha256:a7bb9c01e34a2f116f8f6bcef4351bb8aede6d7c8d95dd4731717287b0fdfb43

Observation 21b96249-913d-4112-89c4-a794bb68a231 · inbound

Surfacing Semantic Orthogonality Across Model Safety Benchmarks: A Multi-Dimensional Analysis cites this paper.

Surfacing Semantic Orthogonality Across Model Safety Benchmarks: A Multi-Dimensional Analysis SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T14:47:15.353466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:47:15.353466Z digest=sha256:6db3a08edaf1ab38a33194ad68111ae6c061f744237f87a9875464470ff283d2

Observation 9864cccf-0cc0-4dd0-ae40-dd1ba2cc2953 · inbound

Evaluating Chinese Large Language Models: The Influence of Persona Assignment on Stereotypes and Safeguards cites this paper.

Evaluating Chinese Large Language Models: The Influence of Persona Assignment on Stereotypes and Safeguards SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T10:36:38.658571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:36:38.658571Z digest=sha256:08428bbcc38664f72646665b5dab2622381978f0c29db450516d1cf379a46854

Observation fffd0edc-3cf8-41c0-959d-51eee22ef52e · inbound

HuggingGraph: Understanding the Supply Chain of LLM Ecosystem cites this paper.

HuggingGraph: Understanding the Supply Chain of LLM Ecosystem SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T16:29:10.437279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:29:10.437279Z digest=sha256:f5e45c421d39e43b92639c208928abe0ca545ca079e71f4786a42418dc2b57f2

Observation 8fbc3005-0f5d-4311-b4d6-a998d370b006 · inbound

Evaluating AI-Generated Images of Cultural Artifacts with Community-Informed Rubrics cites this paper.

Evaluating AI-Generated Images of Cultural Artifacts with Community-Informed Rubrics SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 98

Resolution
verified exact
arxiv_id, observed 2026-05-13T21:03:20.065909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-13T20:59:52.448832Z digest=sha256:24a58953538b58af12d8e8ead8d59afdeae5ee08366fcd0882cc72add646d3e8

Observation e12dbdf0-ab72-48e6-a880-dd1cfc49b092 · inbound

Evaluating AI-Generated Images of Cultural Artifacts with Community-Informed Rubrics cites this paper.

Evaluating AI-Generated Images of Cultural Artifacts with Community-Informed Rubrics SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 98

Resolution
verified exact
arxiv_id, observed 2026-05-21T10:40:00.752462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-21T10:35:39.269869Z digest=sha256:122dd7f4702dd5f7e23fab7eacdd353bc184d688788a6449922d341db4c90a6d

Observation 24c18688-a8fc-4989-bbbd-8a1edae3b3bb · inbound

Safety is Contextual, LLM-Judges Are Not: Navigating the Rigid Priors of Evaluators cites this paper.

Safety is Contextual, LLM-Judges Are Not: Navigating the Rigid Priors of Evaluators SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety

Reference 38

Resolution
metadata mismatch
arxiv_id, observed 2026-06-27T21:41:18.499826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-06-27T21:39:26.268337Z digest=sha256:a2e9cee3f1229e5277aea8f185fac2bbf4f89fed2a52c4a941e4d7491e6ab0ff