This paper proposes ToolCUA, an end-to-end agent designed to learn optimal GUI-Tool path selection through a staged training paradigm, and introduces an Interleaved GUI-Tool Trajectory Scaling Pipeline that repurposes abundant static GUI trajectories and synthesizes a grounded tool library, enabling diverse GUI-Tool tr...
Xuhao Hu, Xi Zhang, Hai-Yang Xu et al.· arXiv.org· 9 citations· ⚡4
This work introduces RecreationWorld, a five-platform framework built around recreation: given a running reference, an agent must discover its behavior and build a faithful implementation with no prescribed workflow, and introduces RecreationBench, comprising 250 diverse tasks across domains and platforms.
Shuai Bai, Jia-Yong Deng, Si-Cheng Fan et al.· 1 citation
Qwen-CUA is introduced, a native computer-use agent with a 397B-A17B Qwen mixture-of-experts backbone that outperforms Qwen3.7 and remains competitive with leading proprietary systems, and scalable verifiable interaction and hybrid tool use as key directions.
Dunjie Lu, Shuai Bai, Tianyi Bai et al.· 2 citations
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