Yuncheng Jiang

Human-engineered black-box optimizers have been eclipsed by a recursive dual-agent system that autonomously evolves both the target optimizer codebase and its own meta-design logic from scratch.

Discrete-WAM enables compositional causal reasoning in autonomous driving, outperforming traditional methods that struggle with complex state-action dynamics.

Latent reasoning can beat explicit Chain-of-Thought – but only if you force it to learn causal dynamics via a visual world model, not just language.