Zhe Li

This review systematically summarizes the development and evolution of big data analysis and artificial intelligence pertaining to intelligent rehabilitation, proposes a four-tier progressive technical architecture, summarizes the standardized governance paradigm of heterogeneous rehabilitation big data, and analyzes the mechanism and application boundaries of artificial intelligence algorithms in rehabilitation scenarios.

EMERGE-Policy reveals that a robot's intelligence can thrive through a collaborative network of specialized agents rather than a monolithic policy.

GameAlpha-2.4K not only revolutionizes RGBA video generation for gaming but also achieves a significant efficiency boost by intelligently bypassing redundant computations.

Replacing standard residual connections with manifold-constrained hyper-connections boosts speaker recognition performance across multiple architectures.

$\omega$-0 enables humanoid robots to seamlessly integrate movement and manipulation, outperforming traditional models by predicting coordinated actions directly from sensory inputs.

Iterative image retrieval can now adapt contextually, achieving a 44.1 R@1 on multi-turn searches—far surpassing previous benchmarks.