Sample Where You Struggle: Sharpening Base Model Reasoning via Entropy-Guided Power Sampling 事件

Sample Where You Struggle: Sharpening Base Model Reasoning via Entropy-Guided Power Sampling arXiv:2606.09926v1 Announce Type: cross Abstract: Sampling from the sequence-level power distribution $p^\alpha$ elicits RL-level reasoning from base language models without any parameter updates, but the standard Metropolis--Hastings (MH), a Markov Chain Monte Carlo (MCMC) sampler, is both expensive and slow-mixing. We trace both to a structural mismatch: $p^\alpha$ mainly departs from $p$ at a sparse,