الباحثون

Chenjia Bai

المنشورات 4

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SMART: Zero-Shot Sim-to-Real Articulated Object Manipulation via Large-Scale Synthetic Pretraining

Jicong Ao, Shuhan Jiang, Yuling Zhong وآخرون · 2026

The ability to interact with articulated objects is essential for embodied intelligent systems, but collecting large-scale real-world demonstrations for these interactions remains challenging due to the precise contact and constraint-following motions involved. Although simulation provides a promising alternative, exis …

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V-JEPA Policy: Building Effective World-Action Models on Predictive Visual Latents

Yang Zhang, Jiangyuan Zhao, Chenyou Fan وآخرون · 2026

World-action models (WAMs) couple future visual-state prediction with action generation. By adapting video generators or image-editing models pretrained at scale, a prominent line of recent WAMs inherits both predictive knowledge and the models in which it was learned. We ask whether a predictive visual latent space in …

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ReWeight: Leveraging Human Data for VLA Post-Training via Demonstration Retrieval and Sample Weighting

Chenwei Wang, Dianye Huang, Match W. L. Ko وآخرون · 2026

Post-training vision-language-action (VLA) models for specific robots and tasks requires in-domain demonstrations, yet collecting diverse robot data is costly. Egocentric human demonstrations provide a scalable alternative, but directly mixing human and robot data can introduce cross-embodiment discrepancies and degrad …

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