103 citations · 228 across the 24 of their papers we have counts for
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cs.RO2024
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…
cs.RO2024★ 69 cited
Real-World Robot Applications of Foundation Models: A Review
Kento Kawaharazuka, Tatsuya Matsushima, Andrew Gambardella +3
Recent developments in foundation models, like Large Language Models (LLMs) and Vision-Language Models (VLMs), trained on extensive data, facilitate flexible application across dif…