ConceptACT: episode-level concepts for sample-efficient robotic imitation learning
Imitation learning enables robots to acquire complex manipulation skills from human demonstrations, but current methods rely solely on low-level sensorimotor data while ignoring the rich semantic knowledge humans naturally possess about tasks. We present ConceptACT, an extension of Action Chunking with Transformers that leverages episode-level semantic concept annotations during training to improve learning efficiency. Unlike language-conditioned approaches that require semantic input at deploym
Record details
Published: 12 August 2026
Source: Frontiers in Robotics and AI
Category: Research
Topics: Agents & autonomy
Retrieved: 12 August 2026
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ethics.ai (12 August 2026), “ConceptACT: episode-level concepts for sample-efficient robotic imitation learning,” evidence record 18473, https://ethics.ai/record/18473 (originally published by Frontiers in Robotics and AI).
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