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Kanata Suzuki

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#machine learning Preprint Oct 2026

Supervise What Decides Success: Criterion-Aligned Auxiliary Losses for Latent World-Model Planning

Latent world models plan by scoring candidate action sequences with distances in latent space. However, task success is judged by physical quantities, which we call the success-criterion quantities. In all four latent world models we examine, the end-effector position is encoded in the latent state with an error larger...

Takumi Hara, Kanata Suzuki · 0 citations
Review Sep 2026

Toward Unified Robot Learning: Bridging Representation, Vision-Language-Action, and World Models

For robots to operate reliably in real-world environments, they need to perceive their surroundings, act, and reason about the consequences of those actions. Rapid progress in the domains of representation learning, VLA models, and world models has significantly enhanced the capabilities of robot learning systems, enab...

Shaunak A. Mehta, Ananya Hazarika, Haochen Zhang et al. · 0 citations

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