Author

Amir Bar

3 papers indexed here

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Preprint Oct 2026

Native Action-Prior Learning from Videos for World Action Models

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...

Zhao-Chong An, Fei Zhang, Meng-Lin Jia et al. · 0 citations

#artificial intelligence Preprint Oct 2026

World Action Modeling with Progressive Visual Planning

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...

Fei Zhang, Zhao-Chong An, Duncan P. Frost et al. · 0 citations

#artificial intelligence Preprint Sep 2026

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

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...

Beomsu Kim, Chieh-Hsin Lai, Bac Nguyen et al. · 0 citations