arXiv cs.LG
· Papers
Depth-Entropy Guided Sampling for Training-Free LLM Reasoning
arXiv:2607.09693v1 Announce Type: new Abstract: Reinforcement learning (RL) has become the dominant paradigm for improving the reasoning capabilities of large language models, but it requires expensive training, curated data, and reward signals. Recent work shows that sampling from sharpened base-model distributions at