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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 13 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 2026-08-13T06:32:02.005865+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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-23T20:58:16.237327Z digest=sha256:fba1a243e56c5c5179c86128a145abd4dd8360024cd4cb61b5608357efaf8e31

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:bdf92faf084bbeec2e0c874e57d4d9688fe8249aa0f72c989fb18df5be8fda18

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=sha256:35861d0a57cb2b19bd67631b68319e69a516406f2540269f0eaf863aefaa2631

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:a08e611679f9db92f2effd895fe1df6a02407b07524fb39e28695ce498f247b7

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:bd1bffaaa7b39d453b136e960df78aba88c49c9b6820d60fdb1beccbde339c6b

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=sha256:5cd5f281ce1ab45d7f0c832cdceb1cd8e630734a26136d6678b1313be5240a85

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:fb288a41485e5949f99c3228cd7e5d5f766ab04351bc798636871a1fe7d231cb

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=sha256:8df271b713ff632840f437f5c805b5d4b3bbdffdea37a20be568fe4a1867015f

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=sha256:6c946b206d6e13e8a888984b9c844b426e23fa16cc3f6c1050e99c34ff39f391

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=sha256:99bc52dbc78ead512bb8f157f111df109d8c84f7f8514ba3ef2fff7a54905fa2

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-13T20:59:52.448832Z digest=sha256:a264c68b3944452df644c05fc8525fde274e51bf03a7102835d4a90e3e3cdff7

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-21T10:35:39.269869Z digest=sha256:32e330f39f11582f5d4aac1e30d23f9209457648f91106129f699926c87bb9c3

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-27T21:39:26.268337Z digest=sha256:f697b8f6d4d874fd5d8160181eff4287b8d9b1bf70a345d481d294eacff46be0