Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Introducing v0.5 of the AI Safety Benchmark from MLCommons
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2404.12241.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-13T18:51:10.298187Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-08T13:54:58.614474Z
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 c95dd37a-65d2-4051-8125-61a75faa3f98 · inbound
WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs cites this paper.
WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs Introducing v0.5 of the AI Safety Benchmark from MLCommons
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T16:25:14.910778Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation b186ba0b-4eae-46e9-bf8c-302d587c38b0 · inbound
A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents cites this paper.
A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents Introducing v0.5 of the AI Safety Benchmark from MLCommons
Reference 74
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T14:12:22.155301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation aa810aa7-4335-41ff-af04-86dc9ad62cf3 · inbound
TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts cites this paper.
TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts Introducing v0.5 of the AI Safety Benchmark from MLCommons
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T09:08:25.508279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation fa4fab60-4f78-4b84-93bc-d09fc322e449 · inbound
S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models cites this paper.
S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models Introducing v0.5 of the AI Safety Benchmark from MLCommons
Reference 126
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T05:41:02.239274Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 00c58042-158f-4070-9cf8-bd4a1b5f5813 · inbound
Learning from Mistakes: Can LLM Self-Recover after Misalignment? cites this paper.
Learning from Mistakes: Can LLM Self-Recover after Misalignment? Introducing v0.5 of the AI Safety Benchmark from MLCommons
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T18:51:10.298187Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a39da39-9fbb-40c8-a675-d0c71f055776 · inbound
Schema-First Retrieval: Embedding Catalogs for Natural Language Analytics cites this paper.
Schema-First Retrieval: Embedding Catalogs for Natural Language Analytics Introducing v0.5 of the AI Safety Benchmark from MLCommons
Reference 50
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-30T10:44:36.734735Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 67b2d984-ff10-4654-afc3-9c2894c5e3cb · inbound
Grounded Optimization: A Layered Engineering Framework for Reducing LLM Hallucination in Automated Personal Document Rewriting cites this paper.
Grounded Optimization: A Layered Engineering Framework for Reducing LLM Hallucination in Automated Personal Document Rewriting Introducing v0.5 of the AI Safety Benchmark from MLCommons
Reference 17
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T21:08:57.557430Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation f13ce255-5e79-4098-beb1-51c6ae9b208c · inbound
Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety cites this paper.
Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety Introducing v0.5 of the AI Safety Benchmark from MLCommons
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T14:28:50.627444Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e3228f3-0038-446b-a377-a6abc999f835 · inbound
Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability cites this paper.
Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability Introducing v0.5 of the AI Safety Benchmark from MLCommons
Reference 88
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-08T13:54:58.615885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.