This bi-yearly research paper list spotlights significant advancements in large language model (LLM) reasoning, primarily driven by sophisticated training strategies. It delves into original research showcasing dramatic improvements in LLM capabilities through innovative methodologies, providing technical professionals with key insights into inference-time scaling, evaluation, and performance optimization, alongside understanding model thought processes. This essential resource for cutting-edge AI development is further complemented by the author's comprehensive Machine Learning Q and AI book, now available for focused study.