Weihao Zhang

A training-free framework that reformulates failure recovery as test-time scaling over causal histories, which decomposes recovery into three coupled decisions: when to revise the causal history, where to recover a reliable history prefix, and which history configuration best supports subsequent execution.

Multi-chiplet architectures can unlock significant speedups and memory savings for low-batch MoE inference by dynamically scheduling expert computations across high-bandwidth die-to-die links.

Scaling LLM-based multi-agent systems doesn't just need better prompts or models, but a whole new software engineering approach focused on managing runtime entropy.