From the 1 of 8 linked papers with an AI index.
8 papers
Qwen-CUA: Native Computer Use for (almost) Everything
Dunjie Lu, Shuai Bai, Tianyi Bai +42
Native computer use offers a general interface for agents to operate almost any software available to people, but requires long-horizon state tracking, large-scale interactive expe…
OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks
Mengqi Yuan, Zilong Zhou, Xinzhuang Xiong +33
The paper presents OSWorld 2.0, a benchmark consisting of 108 long‑horizon, real‑world computer‑use workflows designed to evaluate how well AI agents can handle complex, multi‑step…
CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents
Bowen Wang, Dunjie Lu, Junli Wang +11
Reinforcement learning with verifiable rewards (RLVR) has driven breakthroughs in domains such as math, tool-use, and software engineering, yet its extension to computer-use agents…
Qwen3-VL Technical Report
Shuai Bai, Yuxuan Cai, Ruizhe Chen +61
We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…
VideoAgentTrek: Computer Use Pretraining from Unlabeled Videos
Dunjie Lu, Yiheng Xu, Junli Wang +12
Training computer-use agents requires massive amounts of GUI interaction data, but manually annotating action trajectories at scale is prohibitively expensive. We present VideoAgen…
OpenCUA: Open Foundations for Computer-Use Agents
Xinyuan Wang, Bowen Wang, Dunjie Lu +39
Vision-language models have demonstrated impressive capabilities as computer-use agents (CUAs) capable of automating diverse computer tasks. As their commercial potential grows, cr…