AI RESEARCH
SPIN: Structural LLM Planning via Iterative Navigation for Industrial Tasks
arXiv CS.AI
•
ArXi:2605.14051v1 Announce Type: new Industrial LLM agent systems often separate planning from execution, yet LLM planners frequently produce structurally invalid or unnecessarily long workflows, leading to brittle failures and avoidable tool and API cost. We propose \texttt{SPIN}, a planning wrapper that combines validated Directed Acyclic Graph (DAG) planning with prefix based execution control.