GATS

Researchers have developed GATS, a framework that achieves 100% success rate in agent planning tasks while using zero large language model calls during inference, drastically reducing computational co…

A new planning framework called GATS (Graph-Augmented Tree Search) eliminates the need for LLM calls during inference, achieving a 100% success rate on synthetic planning tasks and outperforming LATS …

A new planning framework called GATS (Graph-Augmented Tree Search) achieves 100% success rate on synthetic planning tasks and a comprehensive stress test spanning 12 scenarios, outperforming LATS (92%…