arXiv Artificial Intelligence

TaReD: Tool-Aware Recursive Decomposition for Long-Horizon Tasks

TaReD: Tool-Aware Recursive Decomposition for Long-Horizon Tasks

Quick summary

arXiv:2610.11268v1 Announce Type: new Abstract: Agents combine reasoning with tools to interact with external systems and complete real-world tasks. Early agents typically interleave reasoning and actions along a single execution chain. On complex tasks, this chain becomes unreliable because growing histories obscure intermediate dependencies and allow early planning errors to propagate. Recursively decomposing a complex task into smaller subtasks offers a natural solution, yet effective decomposition must account for the system's capabilities so that each subtask can be executed by the availa

Key takeaways

  • arXiv:2610.11268v1 Announce Type: new Abstract: Agents combine reasoning with tools to interact with external systems and complete real-world tasks.
  • Early agents typically interleave reasoning and actions along a single execution chain.
  • On complex tasks, this chain becomes unreliable because growing histories obscure intermediate dependencies and allow early planning errors to propagate.

Why it matters

This development shows AI moving deeper into everyday software. Productivity potential should be weighed against price, data permissions, exportability and the preservation of human control.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗