Efficient World Action Model Inference with Adaptive Intermediate States

arXiv:2609.34608 · cs.RO, cs.AI · Submitted 2026-09-28 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/RSIScience/WAMachine

Project page: https://parrotkk.github.io/WAMachine

Terminology

• Residual Rescaling — 28× in this paper
• Observation Rebinding — 26× in this paper
• Consistency — 24× in this paper · explained in 3 episodes
• Transformer — 17× in this paper · explained in 2 episodes
• Adaptation — 7× in this paper · explained in 1 episode
• Ablation — 6× in this paper · explained in 1 episode
• Benchmark — 6× in this paper · explained in 2 episodes
• Closed-Loop Control — 4× in this paper · explained in 3 episodes
• Diffusion Model — 4× in this paper · explained in 8 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• World Model — 3× in this paper · explained in 7 episodes
• Action Chunking — 2× in this paper · explained in 1 episode
• Training-Free Framework — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Action Flow — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 4 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes

Sources

• Diffusion Transformer Policy
• FutureRTC: Real-Time Robot Execution with Anticipatory-Conditioned Action Chunking
• Faster-WAM: Do World Action Models Need Deep Action Modules?
• Fast-WAM: Do World Action Models Need Test-time Future Imagination?
• C$^3$ache: Accelerating World Action Models with Cross Inference Chunk Cache
• $\tau_0$-WM: A Unified Video-Action World Model for Robotic Manipulation

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