The principle of 'Deletion Tuning,' which selectively deletes weights below 0.05% of an AI model to achieve performance comparable to full fine-tuning (FFT). (Photo=arXiv) A research result has emerged showing that it is possible to significantly enhance mathematical reasoning and tool usage capabilities by selectively removing only a fraction of the weights in large language models (LLMs), less than 0.05% of the total. This is notable because it achieves