Freeform Preference Learning for Robotic Manipulation
By Marcel Torne · Paper · cs.RO
Reward design remains a central bottleneck for autonomous robot policy improvement, especially in long-horizon manipulation tasks where sparse success labels provide too little signal and binary preferences collapse many competing notions of quality into one ambiguous signal. We