#artificial intelligence
Jun 2026
StarOR: Synergizing Tree Search and Test-Time Reinforcement Learning for Optimization Modeling
StarOR is a synergistic search-and-adaptation framework that couples MCTS with Test-Time Reinforcement Learning for optimization modeling and attains a 65.0\% average accuracy with a 4B backbone, matching the highest average and outperforming the evaluated same-backbone test-time baselines.
Jiajun Li, Yu Ding, Shisi Guan et al.
· arXiv.org · 0 citations