arXiv cs.LG
· Papers
Stabilized Best-of-$K$ Training for Neural Combinatorial Optimization
arXiv:2608.00296v1 Announce Type: new Abstract: Leader Reward modifies POMO training to emphasize the best trajectory produced by repeated inference. We test a narrow extension: replace its binary leader/non-leader distinction with a stabilized rank signal indexed by a sampling budget $K$. With the POMO architecture, 3