W2S-AlignTree: Enhancing LLM Alignment with Monte Carlo Tree Search at Inference Time

The research introduces W2S-AlignTree, a novel method for improving the alignment of Large Language Models (LLMs) during inference. This approach leverages Monte Carlo Tree Search to guide the alignment process, potentially leading to more reliable and controllable LLM outputs.

• •W2S-AlignTree aims to improve LLM alignment during the inference phase.
• •The method employs Monte Carlo Tree Search for guiding the alignment process.
• •This approach seeks to enhance the reliability and controllability of LLM outputs.