Checkpoints from the real-world arm of the RSM-as-value-function study (rsmrise), trained on the rsmcookingv5 FR3 / Agilex tabletop cooking dataset: 248 teleop episodes, 181530 motion-filtered frames, 2 cameras (global, wrist), success rate 0.202 under the operator's arrival rule ("next.reward > 0 somewhere, i.e. an operator-marked arrival at a reward state [4] (state 4 = pan on grate, tomato in bowl)"). Shared for the robotics collaboration (@jmarangola). This repo is public: no token and no access request are needed to download anything here. It was created private and switched to public on 2026-09-22 so the binaries could be uploaded at all (the account had no private storage headroom…