RESEARCH PAPER
Latent Action Pretraining Through World Modeling
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- WAMs
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- Source review status
- Verified from primary sources
Category review. LAWM jointly trains latent action chunks and a separate next-frame world model, using the predictive objective to pretrain an executable policy. This is a world-model-based policy-training method, not a standalone general tokenizer/backbone. The world model is explicitly removed for downstream policy inference. Reading evidence
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