What Matters for World Modeling in Vision-Language-Action Models?
Integrating world models into Vision-Language-Action models (VLAs) has emerged as a promising direction, enabling policies to anticipate future dynamics beyond reactive observation-to-action mapping. However, existing approaches vary simultaneously in their world representations, integration paradigms, and policy backbones, making it difficult to determine what truly matters for effective world model integration. To disentangle these factors, we categorize existing efforts into four representative paradigms, namely Implicit Future Alignment, Explicit Future Query, MoT Future Expert, and External World Predictor. We instantiate each within a unified framework and systematically evaluate th...
| Authors | Qisen Ma, Yixiang Chen, Yuan Xu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 14 October 2026 |
| Last updated at source | 14 October 2026 |
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