Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Building Safe GenAI Applications: An End-to-End Overview of Red Teaming for Large Language Models
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.01742.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T06:53:48.841077Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T14:13:30.532224Z
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 f40a056d-35c4-456f-a6eb-3e87dfafb64e · inbound
DoubleAgents: Human-Agent Alignment in a Socially Embedded Workflow cites this paper.
DoubleAgents: Human-Agent Alignment in a Socially Embedded Workflow Building Safe GenAI Applications: An End-to-End Overview of Red Teaming for Large Language Models
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T17:11:40.326935Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d3dc09c5-4620-4db3-8127-17a20a2f40a6 · inbound
How Reliable Are AI Attackers Against a Fixed Vulnerable Target? A 400-Run Empirical Study of LLM Penetration Testing Consistency cites this paper.
How Reliable Are AI Attackers Against a Fixed Vulnerable Target? A 400-Run Empirical Study of LLM Penetration Testing Consistency Building Safe GenAI Applications: An End-to-End Overview of Red Teaming for Large Language Models
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T14:13:30.533701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.