Computer-use agents (CUAs) have advanced along two separate lines: graphical interaction and software development through code and the command line. Real digital work requires both, interleaved rather than stacked end to end. We study hybrid CUAs that autonomously decide when to explore an interface, implement software...
Shuai Bai, Jia-Yong Deng, Si-Cheng Fan et al.· 1 citation
Scaling robot data is crucial for building generalist Vision-Language-Action (VLA) models, yet robot trajectories are harder to scale than web-scale image-text data because embodied collection is costly and sparsely covers the physical world. This makes representation quality a central bottleneck: under a fixed robot-d...
Sen-Qiao Yang, Cheng-Yao Wang, Yuxin Chen et al.· 4 citations
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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