Author

Runliang Niu

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#artificial intelligence Preprint Oct 2026

Imagine to Act: High-Fidelity Data Synthesis via Image Editing World Model for Scalable GUI Agent Training

Graphical User Interface (GUI) agents have emerged as a promising paradigm for automating complex digital workflows across diverse applications. However, training highly capable and generalizable agents fundamentally relies on massive, high-fidelity visual-action trajectories, which are notoriously difficult to acquire...

Yong-Xin Ning, Run-Liang Niu, Qianli Xing et al. · 0 citations

Preprint Aug 2026

Beyond Flat Policies: Hierarchical Post-Training for Embodied Agents in Robotic Manipulation

Hierarchical Robotic Control (HiRoC) is proposed, a hierarchical post-training framework that decouples high-level task planning from low-level action execution and aligns the executor with planner-generated subgoals before reinforcement learning, mitigating the distribution misalignment between planning and execution.

He Kong, Ze Chen, Qi Wang et al. · 0 citations