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Paper · arXiv

Exploring the Limits of Combinatorial Generalization in Embodied Manipulation

In embodied manipulation, Vision Language Action (VLA) models can execute atomic skills, but long-horizon manipulation requires recombining these skills without demonstrations for every skill combination. The full instruction route treats skill chaining as long-horizon imitation. In a controlled study, full instruction training on limited skill combination sequences reaches 40.0% ordered success on covered combinations but only 7.7% on recombination, suggesting memorization of sequence templates rather than robust skill recombination. We introduce Hierarchical Subtask Execution (HSE), a diagnostic framework that exposes skill recombination through a shared modular interface over the planner,

AuthorsXupeng Zhang, Yantai Yang, Chang Guo et al.
Primary category
Published11 October 2026
Last updated at source—
hf-daily-papersvision language actionskill recombinationhierarchical subtask executionrobocombinestart state gappose robust task initializationcombinatorial generalization
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