Crafting next-generation foundation models that are not only powerful and trustworthy but also customizable and efficient, catering to a diverse range of existing and emerging applications. Current research focuses on investigating ways to enhance training signals and related training techniques in order to enable smaller LLMs to develop advanced reasoning capabilities usually seen in Large Foundation Models.