Yadnesh Salvi

Story · arXiv

DeReAct: Decomposed Reasoning and Acting for Reliable AI Agents (arXiv)

paper · Story page

A conveyor of small cards runs toward a gate held shut by a separate stamping mechanism. Past the gate, a workbench holds a scale model being rebuilt from collected objects, and a latched box at the end of the line stays closed until the model matches a reference card.

DeReAct takes two jobs away from the acting model: a Critic validates each proposed action before it runs, and a Context Manager rebuilds state from environment evidence and certifies completion. Pass@1 gains on GAIA and SWE-bench Verified reach 6.5 to 7.0 points for Qwen3-Coder-480B, and shrink as the model gets stronger.

In plain words

  • Researchers built a system to check whether artificial intelligence is taking appropriate actions and has really finished a task.
  • One part checks each proposed action before letting it happen.
  • Another checks evidence from the computer to decide what has happened and whether the job is finished.
  • For developers, tests showed these checks most helped less capable artificial intelligence get tasks right on its first try.

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