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insight - Few-shot Imitation Learning
Efficient In-Context Imitation Learning for Robotics using Keypoint Action Tokens and Large Language Models
Large text-pretrained Transformers can effectively act as efficient in-context imitation learning machines for robotics, without the need for any additional training on robotics data.
FLOWRETRIEVAL: Enhancing Few-Shot Imitation Learning Through Flow-Guided Data Retrieval
FLOWRETRIEVAL improves few-shot imitation learning in robotics by retrieving motion-similar data from prior datasets using optical flow representations, leading to more efficient policy learning compared to methods relying solely on visual or semantic similarity.
FLOWRETRIEVAL: 소수 샷 모방 학습을 위한 흐름 기반 데이터 검색
FLOWRETRIEVAL은 이전 데이터에서 유사한 동작을 검색하여 소수 샷 모방 학습을 개선하는 방법으로, 광학 흐름을 활용하여 시각적 유사성에 의존하지 않고 작업 간에 전이 가능한 저수준 동작을 포착합니다.
FlowRetrieval：以流程引導數據檢索實現小樣本模仿學習
本文提出了一種名為 FLOWRETRIEVAL 的新方法，透過利用光流表徵從先前數據集中檢索具有相似運動模式的數據，以改進機器人小樣本模仿學習。
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