Selecting Long-Horizon Trajectories for Reliable and Efficient Terminal-Agent Training.

arXiv:2610.05831v1 Announce Type: cross Abstract: Terminal agents are commonly trained by imitating long teacher trajectories, yet how much of each trajectory to supervise remains unexplored. We study the \emph{supervision horizon}, the number of trajectory to