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7 papers published across 0 labs.
Convex AI compositionality is introduced: a formal representation of the configurations generated by finite AI system populations that uses convex spaces that are compatible with lifecycle reachability across the population and can preserve the formal identity relations between these systems.
Convex AI compositionality is introduced: a formal representation of the configurations generated by finite AI system populations that uses convex spaces that are compatible with lifecycle reachability across the population and can preserve the formal identity relations between these systems.
A regulatory framework is proposed proposing pre-deployment evaluation requirements for the CBN, NITDA, SEC, and the AU, arguing that the identified gap reflects an absence of regulatory specification, not a shortage of technical or financial resources.
This bibliometric analysis aims to characterize the intellectual landscape of this field, which has grown rapidly but remains concentrated among few countries and institutions, with citation impact dominated by capability-testing studies rather than governance-focused scholarship.
