
Researchers at Shanghai Jiao Tong University have recently revealed a groundbreaking method that could fundamentally alter the ways in which Large Language Models (LLMs) are trained. By demonstrating that these models can learn intricate reasoning tasks without vast datasets, the study challenges long-held beliefs. Instead, it suggests that small, well-curated batches of data are sufficient, implicating a paradigm shift in










