Hierarchical Skill Retrieval for Data-Efficient Adaptation of Vision-Language-Action Models
While Vision-Language-Action (VLA) models pretrained on large-scale robot datasets provide a strong foundation for robot manipulation, their performance can degrade when adapted to new tasks with limited task-specific demonstrations. Retrieval offers a practical way to reuse existing demonstrations for data-efficient adaptation, but existing methods often rely on visual similarity, state-action representations, or task-level language matching. These approaches may overlook the hierarchical structure of long-horizon manipulation tasks, where complete task matches are rare but reusable skills are often abundant. To address this challenge, we propose Hierarchical Skill Retrieval (HSR), a ret...
| Authors | Haoran Hao, Shahram Najam Syed, Jeff Schneider et al. |
|---|---|
| Primary category | cs.RO |
| Published | 25 August 2026 |
| Last updated at source | 25 August 2026 |
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