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Dexterous Robotic Piano Playing at Scale
Le Chen, Yi Zhao, Jan Schneider +7
Endowing robot hands with human-level dexterity has been a long-standing goal in robotics. Bimanual robotic piano playing represents a particularly challenging task: it is high-dim…
Generative World Modelling for Humanoids: 1X World Model Challenge Technical Report
Riccardo Mereu, Aidan Scannell, Yuxin Hou +6
World models are a powerful paradigm in AI and robotics, enabling agents to reason about the future by predicting visual observations or compact latent states. The 1X World Model C…
Slot Attention with Re-Initialization and Self-Distillation
Rongzhen Zhao, Yi Zhao, Juho Kannala +1
Unlike popular solutions based on dense feature maps, Object-Centric Learning (OCL) represents visual scenes as sub-symbolic object-level feature vectors, termed slots, which are h…
Extracting Visual Plans from Unlabeled Videos via Symbolic Guidance
Wenyan Yang, Ahmet Tikna, Yi Zhao +4
Visual planning, by offering a sequence of intermediate visual subgoals to a goal-conditioned low-level policy, achieves promising performance on long-horizon manipulation tasks. T…
Discrete Codebook World Models for Continuous Control
Aidan Scannell, Mohammadreza Nakhaei, Kalle Kujanpää +4
In reinforcement learning (RL), world models serve as internal simulators, enabling agents to predict environment dynamics and future outcomes in order to make informed decisions.…
Efficient Reinforcement Learning by Guiding World Models with Non-Curated Data
Yi Zhao, Aidan Scannell, Wenshuai Zhao +7
Leveraging offline data is a promising way to improve the sample efficiency of online reinforcement learning (RL). This paper expands the pool of usable data for offline-to-online…