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20162026
most citedLazy-MDPs: Towards Interpretable Reinforcement Learning by Learning When to Act

4 citations · 6 across the 7 of their papers we have counts for

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cs.AI2022

On the importance of data collection for training general goal-reaching policies

Alexis Jacq, Manu Orsini, Gabriel Dulac-Arnold +3

Recent advances in ML suggest that the quantity of data available to a model is one of the primary bottlenecks to high performance. Although for language-based tasks there exist al…