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WoW: Towards a World omniscient World model Through Embodied Interaction
Published in arXiv preprint (under review), 2025
A 14-billion parameter world model trained on 2 million robot trajectories, demonstrating that physical intuition emerges from large-scale embodied interaction.
Recommended citation: Xiaowei Chi*, Peidong Jia*, Chun-Kai Fan*, ... Zhiyuan Jiang, ... et al. (2025). "WoW: Towards a World omniscient World model Through Embodied Interaction." arXiv preprint arXiv:2509.22642.
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Zoom in, Click out: Unlocking and Evaluating the Potential of Zooming for GUI Grounding
Published in arXiv preprint (under review), 2025
A training-free method that leverages zooming as a powerful prior for GUI grounding, achieving state-of-the-art results across multiple benchmarks.
Recommended citation: Zhiyuan Jiang, Shenghao Xie, Wenyi Li, Wenqiang Zu, Peihang Li, Jiahao Qiu, Siqi Pei, Lei Ma, Tiejun Huang, Mengdi Wang, Shilong Liu. (2025). "Zoom in, Click out: Unlocking and Evaluating the Potential of Zooming for GUI Grounding." arXiv preprint arXiv:2512.05941.
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Wow, wo, val! A Comprehensive Embodied World Model Evaluation Turing Test
Published in arXiv preprint (under review), 2026
The first comprehensive benchmark for embodied world models, examining five core abilities with 22 evaluation metrics and strong correlation with human preference.
Recommended citation: Chun-Kai Fan*, Xiaowei Chi*, ... Zhiyuan Jiang, ... et al. (2026). "Wow, wo, val! A Comprehensive Embodied World Model Evaluation Turing Test." arXiv preprint arXiv:2601.04137.
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