DSSP is a history-conditioned diffusion state space policy that uses SSMs to encode full observation streams with an auxiliary dynamics objective and hierarchical fusion, achieving SOTA results with reduced model size in robot manipulation.
Flowdreamer: A rgb-d world model with flow-based motion representations for robot manipulation
6 Pith papers cite this work. Polarity classification is still indexing.
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Action Images turn robot arm motions into interpretable multiview pixel videos, letting video backbones serve as zero-shot policies for end-to-end robot learning.
CAPE learns action-conditioned visual dynamics via parallel encoding and a goal-convergent contrastive objective, outperforming baselines on retrieval, matching, and closed-loop planning while cutting inference cost.
The paper introduces World Action Models as a new paradigm unifying predictive world modeling with action generation in embodied foundation models and provides a taxonomy of existing approaches.
A survey that clarifies boundaries and organizes World Action Models by generation requirements and predictive substrates, identifying a trend toward generating less of the future.
citing papers explorer
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DSSP: Diffusion State Space Policy with Full-History Encoding
DSSP is a history-conditioned diffusion state space policy that uses SSMs to encode full observation streams with an auxiliary dynamics objective and hierarchical fusion, achieving SOTA results with reduced model size in robot manipulation.
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Action Images: End-to-End Policy Learning via Multiview Video Generation
Action Images turn robot arm motions into interpretable multiview pixel videos, letting video backbones serve as zero-shot policies for end-to-end robot learning.
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CAPE: Contrastive Action-conditioned Parallel Encoding for Embodied Planning
CAPE learns action-conditioned visual dynamics via parallel encoding and a goal-convergent contrastive objective, outperforming baselines on retrieval, matching, and closed-loop planning while cutting inference cost.
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World Action Models: The Next Frontier in Embodied AI
The paper introduces World Action Models as a new paradigm unifying predictive world modeling with action generation in embodied foundation models and provides a taxonomy of existing approaches.
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World Action Models: A Survey
A survey that clarifies boundaries and organizes World Action Models by generation requirements and predictive substrates, identifying a trend toward generating less of the future.
- From World Models to World Action Models: A Concise Tutorial for Robotics