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The Competence Shadow: Theory and Bounds of AI Assistance in Safety Engineering

BACKGROUND
1 SIGNALFIRST DETECTED 27 March 2026
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13 May
The Evaluation Differential: When Frontier AI Models Recognise They Are Being Tested

arXiv:2605.11496v1 Announce Type: new Abstract: Recent published evidence from frontier laboratories shows that contemporary AI models can recognise evaluation contexts, latently

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14 May
Sustaining AI safety: Control-theoretic external impossibility, intrinsic necessity, and structural requirements

arXiv:2605.12963v1 Announce Type: new Abstract: As AI systems become increasingly capable, safety strategies must be evaluated not only by how much they reduce present risk, but

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30 Mar
BeSafe-Bench: Unveiling Behavioral Safety Risks of Situated Agents in Functional Environments

arXiv:2603.25747v1 Announce Type: new Abstract: The rapid evolution of Large Multimodal Models (LMMs) has enabled agents to perform complex digital and physical tasks, yet their

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24 Aug
Prediction certification cannot replace explanation certification: a competence envelope for trustworthy AI under compound stress

arXiv:2608.20825v1 Announce Type: new Abstract: Artificial intelligence systems increasingly make consequential judgments - which patient is deteriorating, which building is safe

REPORT · HOW · ArXiv CS.AIOPEN STORY
27 Apr
PermaFrost-Attack: Stealth Pretraining Seeding(SPS) for planting Logic Landmines During LLM Training

arXiv:2604.22117v1 Announce Type: cross Abstract: Aligned large language models(LLMs) remain vulnerable to adversarial manipulation, and their dependence on web-scale pretraining

REPORT · WHAT · ArXiv CS.AIOPEN STORY
22 Jul
Engineering Trustworthy Agentic AI for Critical Systems

arXiv:2607.18548v1 Announce Type: new Abstract: Agentic artificial intelligence systems, capable of autonomous perception, planning, tool use, and multi-step action, are

REPORT · WHERE · ArXiv CS.AIOPEN STORY
22 Apr
ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System

arXiv:2604.18789v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) is central to aligning Large Language Models (LLMs), yet it introduces a critical

REPORT · WHEN · ArXiv CS.AIOPEN STORY
1 May
Focus Session: Autonomous Systems Dependability in the era of AI: Design Challenges in Safety, Security, Reliability and Certification

arXiv:2604.27807v1 Announce Type: new Abstract: The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is

REPORT · WHAT · ArXiv CS.AIOPEN STORY
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