V-Simba improves architectural efficiency for reinforcement learning in visual continuous control
Read the original at arxiv.org→arXiv:2608.07870v1 Announce Type: new Abstract: Improving sample efficiency remains a core challenge in reinforcement learning (RL), especially in real-world settings like robotics, where data collection is costly....
Original headline: "V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control"
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- Aug 11, 04:00 UTC arXiv cs.LG lead source V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control