Binary-reward RL hits 94% success on hard robotics task, recipe looks clear
kastnerkyle · x · 2026-11-11
Researcher SediBY571 reports that a robot policy trained with pure binary rewards reached >94% success rate at 7B training steps, jumping from 79% to 94% in the final 2B steps.
A benchmark chart compares three reward setups (3 seeds each): dense reward with nominal resets (98%), sparse reward + reset bank + SGS (98%), and binary reward + reset bank + SGS (94%). The takeaway: even with only success/fail signal, reset bank + SGS lets RL solve complex robotics tasks near the ceiling, with an accompanying article arguing RL can tackle hard robotics tasks.
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