Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T21:16:13.354682Z
Paper Citation Record · LEDGER
As of 18 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 0 inbound Pith citation observations for arXiv:2411.08981.
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, observed 2026-08-12T21:16:13.354682Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
74 of 74 outbound references displayed
External citation measurements
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Al-Khalifa, and Abdel Magid Hamouda
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems AI Oversight and Human Mistakes: Evidence from Centre Court
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Kilr Ayyub, Bilal M
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Probabilistic Risk Analysis: Foundations and Methods
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Dynamic Adversarial Attacks on Autonomous Driving Systems
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Collins, Matthew Barker, et al
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Explicit deepfake images of taylor swift elude safeguards and swamp social media, January 26, 2024
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Scalable watermarking for identifying large language model outputs
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Compl-ai framework: A technical interpretation and llm benchmarking suite for the eu artificial intelligence act, 2023
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems On the democratic role of news recommenders
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Woods, and Nancy Levensen
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Accelerated life testing (ALT) design based on computational reliability analysis
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Should artificial intelligence have lower acceptable error rates than humans? Insights into Imaging, 14(1):79, 2023
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems A family of software reliability models with bathtub-shaped fault detection rate
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Reliability, Resilience and Human Factors Engineering for Trustworthy AI Systems Collision between vehicle controlled by developmental automated driving system and pedestrian
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