A language model is designed to solve complex logic puzzles by generating a step-by-step reasoning path. It uses a decoding strategy where it builds a tree of possible reasoning steps, randomly samples different paths to explore, and uses a separate scoring mechanism to estimate how likely each partial path is to lead to a correct final answer. The model is observed to explore a wide variety of paths but consistently fails to solve the puzzles, often pursuing steps that are logically unsound. What is the most likely deficiency in this system?

A language model is generating a response using a search technique that builds a tree of possibilities. The process involves repeatedly selecting promising paths, expanding the tree with new options, simulating random completions to estimate their quality, and then updating the value of the explored paths based on those outcomes. Arrange the following four core steps of a single iteration of this search process into the correct logical sequence.

Choosing a Decoding Strategy for Complex Reasoning