CAA-X V4: Cognitive Architecture eXtension for Zero-Shot Agent Challenges

This preprint presents CAA-X V4, a cognitive architecture extension framework addressing the 'Intention Gap' in current end-to-end large models. Building upon Global Workspace Theory (Baars, 1988) and predictive processing (Friston, 2010), CAA-X introduces: (1) Cognitive Atoms as weakly-coupled functional primitives with zero-shot compositional generalization; (2) Predictive Tension Fields as holographic world models; (3) GWP Protocol Engine with selective synchronization; (4) Cognitive Manifold Trajectory Planning with intention-biased geodesics; (5) Lambda-Order Parameter for dynamic resource allocation. Empirical validation includes a robotic arm grasping experiment achieving 78% zero-shot success rate. This work responds to the emerging deflationary trend in AI research (ICLR 2026, NeurIPS 2025) that rewards mechanistic explanations and modular architectures over pure scaling. Supplementary analysis integrates 14 top-tier papers published between 2025-2026, identifying CAA-X's alignment with three major field trends: deflationary findings, mechanistic explanations, and modular architecture revival.