Dreamer 4 is the first agent to obtain diamonds in Minecraft from only offline data by reinforcement learning inside a scalable world model that accurately predicts game mechanics.
Mastering diverse control tasks through world models.Nature, pages 1–7
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
representative citing papers
Converting 3D MRI volumes into action-conditioned 2D slice navigation sequences offers a complementary self-supervised pretraining signal for learning anatomical and spatial representations.
WorldArena 2.0 extends embodied world model benchmarks to visuotactile perception, interactive policy training, and diverse real and simulated robotic platforms under a unified protocol.
OrbiSim builds a differentiable physics engine from world models to support gradient-based policy optimization and contact modeling in robotics.
citing papers explorer
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Training Agents Inside of Scalable World Models
Dreamer 4 is the first agent to obtain diamonds in Minecraft from only offline data by reinforcement learning inside a scalable world model that accurately predicts game mechanics.
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3D MRI Image Pretraining via Controllable 2D Slice Navigation Task
Converting 3D MRI volumes into action-conditioned 2D slice navigation sequences offers a complementary self-supervised pretraining signal for learning anatomical and spatial representations.
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WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform
WorldArena 2.0 extends embodied world model benchmarks to visuotactile perception, interactive policy training, and diverse real and simulated robotic platforms under a unified protocol.
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OrbiSim: World Models as Differentiable Physics Engines for Embodied Intelligence
OrbiSim builds a differentiable physics engine from world models to support gradient-based policy optimization and contact modeling in robotics.