34 citations · 114 across the 13 of their papers we have counts for
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cs.LG2024
ReLIC: A Recipe for 64k Steps of In-Context Reinforcement Learning for Embodied AI
Ahmad Elawady, Gunjan Chhablani, Ram Ramrakhya +4
Intelligent embodied agents need to quickly adapt to new scenarios by integrating long histories of experience into decision-making. For instance, a robot in an unfamiliar house in…
cs.LG2020★ 34 cited
La-MAML: Look-ahead Meta Learning for Continual Learning
Gunshi Gupta, Karmesh Yadav, Liam Paull
The continual learning problem involves training models with limited capacity to perform well on a set of an unknown number of sequentially arriving tasks. While meta-learning show…