
Innovative advancements in the field of large language models (LLMs) are emerging, thanks to collaborative efforts between UC Berkeley and Google Research. In a groundbreaking study, researchers have unveiled a novel yet straightforward test-time scaling approach that significantly enhances the reasoning capabilities of LLMs. This method, which relies on scaling up sampling-based search techniques, generates multiple responses and utilizes the