AIBullisharXiv – CS AI · 6h ago6/10
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RoboSSM: Scalable In-context Imitation Learning via State-Space Models
Researchers introduce RoboSSM, a new in-context imitation learning framework that replaces Transformers with state-space models (SSMs) for robotic task learning. The approach demonstrates superior performance on long-context prompts and achieves better generalization to unseen tasks compared to Transformer-based methods, establishing SSMs as a viable alternative backbone for robot learning systems.