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cs.RO2026
Advantage-Driven Explicit Memory for Social Navigation
Yeonsoo Park, Mattia Racca, Guillaume Bono +4
Robot policies are predominantly learned with classical parametric variants of imitation learning or RL, where training stores the agent's behavior exclusively in the policy's netw…
cs.CV2026
Compressing History into Memory: Distilling Transformers into Recurrent Transformers
Philippe Weinzaepfel, Christian Wolf, Bülent Mert Sariyildiz +3
Transformers are AI's workhorse but their computational cost becomes prohibitive when processing long sequences. We target long-horizon streaming vision and robotics applications,…
cs.RO2026
A scalar per patch from pre-trained ViTs enables fast moving navigation in the real world
Steeven Janny, Leonid Antsfeld, Christian Wolf
Trained policies for real-world robotics rely on computer vision components, typically in the form of pre-trained visual encoders. These encoders are an essential component and it…