Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2410.07959.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:45:01.720588Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T09:57:00.691632Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 18968b68-ef8f-4c59-8ec1-69467b5a8c12 · inbound
A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Reference 232
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1ca1663f-e8b9-4ce7-9873-268c1456183e · inbound
Attestable Audits: Verifiable AI Safety Benchmarks Using Trusted Execution Environments COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Reference 29
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 232edc08-05fc-4859-ae8c-82d5204efa6b · inbound
AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7bc503b2-076e-41f3-ab3b-72eaf90a0254 · inbound
Swiss-Bench 003: Evaluating LLM Reliability and Adversarial Security for Swiss Regulatory Contexts COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 81fd9744-4afa-4e10-bd14-8bb553e7aa52 · inbound
Meta-Benchmarks for Financial-Services LLM Evaluation COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4d7027e0-d598-417e-b515-4306f895bdd8 · inbound
Reverse Engineering Compliance: A Dual-Graph Verification Framework for Auditing Legacy IT Security Concepts COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4e9ca873-9a3b-4e68-ba1c-8295710a7627 · inbound
Do Generative AI Assistants Respect robots.txt? Tracing Web Access Beyond Visible Answers COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.