Generalgeneralizable
Generalgeneralizable is an adjective used in artificial intelligence, cognitive science, and philosophy to describe a property where an agent, model, or theory can apply its learned or established behavior across a wide range of tasks, domains, and data distributions. The term emphasizes breadth of applicability and resilience to distribution shifts, beyond the conditions under which it was originally developed.
As a neologism, generalgeneralizable is a portmanteau-like blending of generality and generalizability, sometimes repeated to stress
In practice, assessing generalgeneralizable capabilities involves cross-domain evaluation, zero-shot or few-shot transfer, and robustness to changes
Critiques note that achieving broad coverage in one benchmark does not guarantee genuine generalization, and that
Related concepts include generalization, transfer learning, meta-learning, robustness, and domain adaptation. In literature, generalgeneralizable remains a