الباحثون

Amir Bar

المنشورات 3

نسخة أولية وصول مفتوح

Native Action-Prior Learning from Videos for World Action Models

Zhaochong An, Fei Zhang, Menglin Jia وآخرون · 2026

World action models integrate future visual dynamics with robot action prediction, but their scalability remains limited by the need for action-annotated robot trajectories. Observation-only videos contain rich evidence about interaction dynamics, but existing approaches typically use them either to pretrain visual rep …

نسخة أولية وصول مفتوح

World Action Modeling with Progressive Visual Planning

Fei Zhang, Zhaochong An, Duncan Frost وآخرون · 2026

World action models (WAMs) have emerged as a promising paradigm for robotic control by jointly predicting future visual dynamics and actions from an initial observation and instruction. However, existing WAMs struggle with long-horizon prediction, as generating dense video rollouts is highly inefficient. Some recent WA …

نسخة أولية وصول مفتوح

Learning What to Recall: Adaptive Multi-Cue Episodic Memory for World Models

Beomsu Kim, Chieh-Hsin Lai, Bac Nguyen وآخرون · 2026

World models predict future observations from current experience and actions, yet prediction can depend on observations seen far in the past. Episodic memory preserves past observations for later recall; however, as memory accumulates, it raises a fundamental question: which memories are useful for the current predicti …

المؤلفون المشاركون