# DeepSearch-World Trains Tool-Use Agents to Improve From Their Own Experience

The method uses self-distillation inside a verifiable environment to escape the reliance on fixed teacher trajectories and sparse reinforcement learning (RL) rewards.

- Published: 2026-07-10T05:31:45.551Z
- Canonical: https://polylog.news/ai/2026-07-10/deepsearch-world-trains-tool-use-agents-to-improve-from-thei
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [arXiv (cs.CL)](https://arxiv.org/abs/2607.07820)

A new arXiv paper, DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment, targets a core bottleneck in training tool-use agents. Supervised fine-tuning relies on fixed trajectories distilled from a teacher m…

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