asynchronous-execution

AHA-WAM is an asynchronous world-action model that uses dual Diffusion Transformers to decouple world prediction from action execution, achieving efficient long-horizon planning and real-time control. It achieves state-of-the-art performance on robotic manipulation tasks with up to 92.8% success on RoboTwin and 78.3% on real-world tasks, while reaching 24.17 Hz closed-loop control.

FlashEvolve is a framework that accelerates LLM-based agent self-evolution by using asynchronous stage orchestration and artifact version tracking. It significantly improves throughput and token efficiency compared to synchronous execution methods.