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artificial intelligence

18,165 papers

#artificial intelligence Open access Oct 2026

AI CLOSED-LOOP QUANTUM-NANO FABRICATION AND VERIFICATION AT THE LIMIT Physical Observation × Bounded Decision × Verified Closure This research monograph develops an exploratory engineering architecture for the use of artificial intelligence in nanofabrication workflows where physical evidence, authorization, quality verification, and recovery must remain distinct. Its fundamental claim is modest but consequential: a model-generated recipe proposal should not become an executable manufacturing instruction merely because an optimization objective improved. Every proposed intervention requires a declared physical operating domain, a traceable observation chain, explicit authority, resource and risk bounds, independent verification, and a recoverable failure pathway.

AI CLOSED-LOOP QUANTUM-NANO FABRICATION AND VERIFICATION AT THE LIMITPhysical Observation × Bounded Decision × Verified Closure This research monograph develops an exploratory engineering architecture for the use of artificial intelligence in nanofabrication workflows where physical evidence, authorization, quality ver...

33 · 0 citations
#artificial intelligence Open access Oct 2026

Cultural Journalism in Germany, 1815–1848: A Critical Anthology. By SeanFranzel and MichaelSwellander (Eds.), Camden House, 2025. 442 pp. $130.00 (hardcover)

A Critical Anthology, editors Sean Franzel and Michael Swellander present a diverse collection of nineteenth-century perspectives that reflect and assess the past, present, and future potential of cultural journalism in the German Confederation.The anthology features thirty-one English-language translations of the prim...

Matthew O. Anderson · 0 citations
#artificial intelligence Open access Oct 2026

Developmental Evaluation for Strengthening Digital Ecosystem Readiness: A Policy Analysis of Coding and Artificial Intelligence Implementation in Vocational Schools in Bangka Belitung Province, Indonesia

The integration of coding and Artificial Intelligence (AI) into vocational education is essential for equipping students with 21st-century digital competencies, yet implementation in remote and island regions like Bangka Belitung archipelago province remains fragmented and unsustainable. This study employs Developmenta...

Peitrik Iwan, Nikmarijal, Suparta · 0 citations
#artificial intelligence Open access Oct 2026

Do Judges Behave like Algorithms?

What if judges already behave like algorithms? As artificial intelligence and algorithms are deployed in many settings, including the judicial system, many have debated whether judges should be allowed to rely on them. We suggest this debate about the role of algorithms in the justice system tracks a longstanding debat...

Riya Manchanda, Eric Chen, Chloe Zhu et al. · 0 citations
#artificial intelligence Open access Oct 2026

A Chain Is Only as Strong as Its Weakest Link: A Scoping Review of System Integration Audits in AI

As artificial intelligence (AI) systems are integrated into diverse interfaces and applications, model-centric audits are insufficient to address risks arising from their deployment. In safety-critical domains such as aerospace, system integration has long been a focal point for technical system audits. Yet, its role i...

Leah Davis, Dominic Martin, AJung Moon · 0 citations
#artificial intelligence Open access Oct 2026

AI from the Margins (AIM): Rethinking Participatory AI Design Through the Lived Experience of Minoritized Communities

Artificial intelligence (AI) can reproduce and amplify the structural inequities faced by minoritized communities. Participatory AI has been proposed as a response, but participation typically starts after problem definitions and success criteria have been set, leaving limited room for minoritized communities to reshap...

Tijs Portegies, Laureanne Willems, Maaike Harbers et al. · 0 citations
#artificial intelligence Open access Oct 2026

Explainable AI Isn’t Enough! Rethinking Algorithmic Contestability

Machine learning systems increasingly make life-changing decisions about individuals, such as loan approvals, hiring, and cheating detection, raising a pressing question: how can individuals respond to negative decisions made by these opaque systems? While explainable artificial intelligence (XAI) has largely focused o...

Timo Freiesleben, Kristof Meding, Gunnar König · 0 citations
#artificial intelligence Review Open access Jan 2027

What's New in Hand and Wrist Arthroscopy: Indications, Techniques, and Emerging Applications.

This review summarizes contemporary evidence, evolving indications, technical innovations, and future directions in wrist arthroscopy, highlighting its growing role as a central component of modern hand and wrist surgery.

Parker H. Johnsen, A. B. Chhabra, Brent R. DeGeorge · 0 citations
#artificial intelligence Preprint Open access Oct 2026

STAIR: Effective Incident Response Using an End-to-End Agentic Planning Framework

Incident response planning is critical for restoring compromised software systems. Existing AIOps methods automate fault diagnosis and remediation and adapt response using feedback, but lack a unified decision basis across planning and execution. This limits their ability to maintain incident state and align actions wi...

Hanlin Jiang, Jionghao Huang, Shaofei Li et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Robustness of Reinforcement Learning-Based Congestion Management in Low-Voltage Grids

Increases in photovoltaic generation, charging of electric vehicles and heat-pump demand challenge operating limits in low-voltage distribution grids. This requires curative curtailment methods that can operate under sparse observability, noisy measurements, and imperfect grid models. Unlike prior end-to-end reinforcem...

Josef Hoppe, Sarra Bouchkati, Farah Nasr et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Improving Certified Robustness via Adversarial Distillation

Certified training aims to produce models whose predictions can be formally verified against adversarial perturbations, typically by optimising upper bounds on the worst-case loss over an allowed perturbation set. For neural networks, certified training methods based purely on tight relaxation bounds produce networks t...

Matteo Melis, Jesus Martinez Del Rincon, Vishal Sharma · 0 citations

The Spec Growth Engine: Spec-Anchored, Code-Coupled, Drift-Enforced Architecture for AI-Assisted Software Development

The Spec Growth Engine is presented, a lightweight framework that addresses both failure modes through a machine-readable spec graph whose nodes carry explicit contract/design separation, a Spine context assembler that scopes agent context to an ownership path, a vertical-slice growth protocol that enforces hardest-fir...

H. Grabowski · 2 citations

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