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Frontier generalist computer-use agents, previously closed-source, are now open for systematic study and community development, with the first release achieving significant performance gains.
Training GUI agents in mocked environments yields substantial real-world performance gains, bridging the gap between simulation and physical device interaction.
Qwen-UI-Agent outperforms leading models in mobile and cross-platform tasks, achieving up to 97.5% accuracy on key benchmarks.
InnerZoom cuts end-to-end latency by up to 31.8% while surpassing existing GUI grounding methods, proving that less can indeed be more.
A 7B parameter model, guided by a novel RL framework, can now generate multi-page websites that rival the functionality of a 671B parameter model, while surpassing it in visual appeal.