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CUA-Universe: A Scalable and Dynamic Environment for Hybrid GUI+CLI Agents

Research LLM Agents

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Merged summary

TL;DR - CUA-Universe is a scalable pipeline for building environments and training data for computer-use agents that coordinate GUI perception with efficient CLI execution. A trained 9B model substantially improved task success while reducing interaction steps and token use across multiple benchmarks.

  • App-Forge converts real desktop software into reproducible virtual machines with discovered, wrapped, or generated command-line interfaces, covering 16 applications.
  • Task-Weave synthesizes hybrid GUI+CLI tasks with controllable difficulty, while Path-Steer generates and verifies efficient trajectories for post-training.
  • On CUA-Verse, the 9B model gained 39.3 score points while using 37% fewer steps and 60% fewer tokens.
  • It also improved OSWorld success rate by 16.8 points and OSWorld-MCP score by 7.84 points, with sizable efficiency gains on both.

Sources (1)

CUA-Universe: A Scalable and Dynamic Environment for Hybrid GUI+CLI Agents

arXiv cs.AI Haoting Shi, Wenhao Wang, Weicheng Fang, Yaozhong Liang, Tian Jin, Pengxiang Zhao, Guangyi Liu, Siheng Chen, Yanfeng Wang 2026-09-04 arXiv:2609.05374
Public signals Semantic Scholar citations 0 · Semantic Scholar influential citations 0
Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · Citations 0 · Influential citations 0 X · N/A Fetched 2026-09-22 14:25:30.660700 UTC

TL;DR - CUA-Universe is a scalable pipeline for building environments and training data for computer-use agents that coordinate GUI perception with efficient CLI execution. A trained 9B model substantially improved task success while reducing interaction steps and token use across multiple benchmarks.

  • App-Forge converts real desktop software into reproducible virtual machines with discovered, wrapped, or generated command-line interfaces, covering 16 applications.
  • Task-Weave synthesizes hybrid GUI+CLI tasks with controllable difficulty, while Path-Steer generates and verifies efficient trajectories for post-training.
  • On CUA-Verse, the 9B model gained 39.3 score points while using 37% fewer steps and 60% fewer tokens.
  • It also improved OSWorld success rate by 16.8 points and OSWorld-MCP score by 7.84 points, with sizable efficiency gains on both.
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