Toward Unified Robot Learning: Bridging Representation, Vision-Language-Action, and World Models
Classification
View four quadrants- Major category
- Related resources
- Quadrant
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- Architecture
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- Prediction paradigm
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- Subcategories
- Surveys & perspectives
- Source review status
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Category review. A 2026 survey of representations, VLA policies, world models and integration interfaces. It is useful context for interpreting WAM scope and evaluation, rather than a pre-2026 foundation or a specific WAM method. The paper is retained for its adjacent resource/method role; WAM joint-prediction/IDM architecture quadrants do not apply to the cataloged contribution. Reading evidence
Contribution
This survey organizes robot learning around representations that encode the environment, VLA policies that generate actions, and world models that predict consequences. Its useful contribution is a vocabulary for tracing how information and feedback cross those interfaces. Integration can remain modular; the authors argue that its value should be demonstrated through improved behavior under uncertainty, distribution shift and temporal dependencies. A small original CALVIN video-prediction diagnostic illustrates hidden-object and collision failures, but supplies no quantitative proof that a unified architecture resolves them.
Abstract
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Affiliations
Fujitsu Research of America; Carnegie Mellon University; Fujitsu Limited