Predicting and improving test-time scaling laws via reward tail-guided search

Muheng Li, Jian Qian, Wenlong Mou

Test-time scaling has emerged as a critical avenue for enhancing the reasoning capabilities of Large Language Models (LLMs). Though the straight-forward ''best-of-$N$'' (BoN) strat…