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cs.AI2026

MAI-Gym: An Open All-in-One Platform for GUI Agent Evaluation and RL Training across Mobile and Computer Environments

Panrong Tong, Quyu Kong, Pengxiang Li +12

Online reinforcement learning (RL) with verifiable rewards has driven rapid progress in mathematics, coding, and tool use, but scaling this success to GUI agents remains challengin…

cs.AI2026

From Tapping to Hopping: Augmenting Mobile GUI Agents with App-Native Deeplinks

Yuchen Sun, Chenglin Cai, Gongjie Zhang +8

Mobile GUI agents complete tasks using GUI actions like taps and swipes. These actions are broadly applicable across applications, but reaching a navigation interface. A single dee…

cs.AI2026

Qwen-Planner-Agent: A Closed-Loop AI-for-AI Framework for Real-World Mobile Planner Agents

Tingyu Qu, Weigao Sun, Yuecheng Liu +23

The rapid progression of large language models is extending AI from passive content generation into the active workflows of engineering and scientific discovery. This shift raises…

cs.AI2026

MobilePA-Bench: Benchmarking Mobile Planner Agents on Complex Real-World Tasks

Yi Zhu, Xiongwei Wu, Qiyi Wang +8

Mobile planning requires a central agent to coordinate tools, persistent user context, reusable procedures, and specialized sub-agents while adapting to execution feedback. Evaluat…

cs.AI2026

Qwen-UI-Agent Technical Report: Toward Next-Generation Real-World Centric Foundation GUI Agents

Hanzhang Zhou, Panrong Tong, Xu Zhang +13

GUI agents have the potential to become a general purpose executor over existing digital devices. To advance them toward real-world use, we envision agents that operate reliably on…

cs.AI2026

Omni-Decision: Evidence-Ledger Planning for Omni-Modal Agents

Ming Ma, Yi Zhu, Yiran Zhong +7

Omni-modal agents must seek evidence across video, audio, web pages, and computation to answer questions. Their main bottleneck is planning: noisy multimodal observations accumulat…