DeReAct: Decomposed Reasoning and Acting for Reliable AI Agents

Lectura rápida

arXiv:2610.02351v1 Announce Type: new Abstract: ReAct-based agents typically rely on a single LLM policy to propose actions, interact with the environment, and decide when a task is complete. This coupling makes action authorization and completion control difficult to enforce independently, allowing errors to propagate and unsupported completion claims to te

Tramo Uno resume esta señal para que entiendas qué ocurrió antes de decidir si quieres revisar la cobertura completa en la fuente original.