Ontological Knowledge Blocks formalize regulatory obligations as 5-tuples linking RDF/OWL schemas, SHACL rules, evidence requirements and provenance, with a compiler enabling profile-based validation demonstrated in an HPC allocation scenario.
The Ethics of AI Ethics: An Evaluation of Guidelines
4 Pith papers cite this work. Polarity classification is still indexing.
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Insider action research in an AI startup identifies three patterns of how practitioners view regulatory requirements and proposes internal expert collaboration as a way to turn external governance rules into shared, practical ownership.
LLM agents use a Cartesian split between learned prediction and engineered control, enabling modularity but creating sensitivity and bottlenecks unlike integrated biological systems.
The survey identifies a key tension in multilingual vision-language models between language neutrality via contrastive learning and cultural awareness via diverse data, with most benchmarks relying on translation-based evaluation.
citing papers explorer
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Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems
Ontological Knowledge Blocks formalize regulatory obligations as 5-tuples linking RDF/OWL schemas, SHACL rules, evidence requirements and provenance, with a compiler enabling profile-based validation demonstrated in an HPC allocation scenario.
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Engaged AI Governance: Addressing the Last Mile Challenge Through Internal Expert Collaboration
Insider action research in an AI startup identifies three patterns of how practitioners view regulatory requirements and proposes internal expert collaboration as a way to turn external governance rules into shared, practical ownership.
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The Cartesian Cut in Agentic AI
LLM agents use a Cartesian split between learned prediction and engineered control, enabling modularity but creating sensitivity and bottlenecks unlike integrated biological systems.
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Multilingual Vision-Language Models, A Survey
The survey identifies a key tension in multilingual vision-language models between language neutrality via contrastive learning and cultural awareness via diverse data, with most benchmarks relying on translation-based evaluation.