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Siteng Huang

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#machine learning Preprint Aug 2026

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance

General-purpose reward models are increasingly the bottleneck for scaling robot learning, yet the recipe for learning value-related capabilities from large-scale heterogeneous corpora remains underexplored. Existing approaches tie supervision to task-internal anchors such as preferences or normalized progress, none of...

Dongchi Huang, Hong-Yin Zhang, Bo-Han Hou et al. · 7 citations
Preprint Jul 2026

RynnWorld-4D: 4D Embodied World Models for Robotic Manipulation

RynnWorld-4D is introduced, a generative model that co-produces future RGB frames, depth maps, and optical flow from a single RGB-D image and a language instruction within one unified diffusion process, and achieves state-of-the-art performance on real-world dexterous bimanual manipulation tasks, particularly excelling...

Haoyu Zhao, Xingyue Zhao, Siteng Huang et al. · 1 citation
Preprint Jul 2026

RynnWorld-Teleop: An Action-Conditioned World Model for Digital Teleoperation

Digital teleoperation, a paradigm that decouples data collection from physical constraints by replacing the real robot with a generative world model, is introduced in RynnWorld-Teleop, a system that integrates depth-aware skeletal conditioning, progressive human-to-robot training on a video Diffusion Transformer, and s...

Haoyu Zhao, Xingyue Zhao, Hangyu Li et al. · 0 citations

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