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Visual Planning

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Jul 7, 2026 · Artificial Intelligence

Is Your World Model Too Slow? Fast‑LeWM Boosts Dynamic Prediction by 4× with Action‑Prefix Parallelism

Fast‑LeWM replaces the step‑by‑step rollout of traditional world models with trajectory‑level parallel prediction using an action‑prefix encoder, raising planning success from 85.8% to 90.5% (92% with self‑consistency) and cutting dynamics time from 31.4 s to 8.0 s, a four‑fold speedup.

Action PrefixCEMParallel Prediction

0 likes · 8 min read

Is Your World Model Too Slow? Fast‑LeWM Boosts Dynamic Prediction by 4× with Action‑Prefix Parallelism

Data Party THU

Mar 4, 2026 · Artificial Intelligence

Can Hyperbolic Embeddings Boost Multi‑Step Visual Planning? Introducing GeoWorld

GeoWorld tackles the geometric neglect and multi‑step shortcomings of energy‑based predictive world models by mapping latent representations onto hyperbolic manifolds and applying a geometry‑aware reinforcement learning framework, achieving notable success‑rate gains on long‑horizon visual planning benchmarks.

Energy-Based ModelsVisual Planninggeometric reinforcement learning

0 likes · 9 min read

Can Hyperbolic Embeddings Boost Multi‑Step Visual Planning? Introducing GeoWorld