Tiny Brains, Giant Impact: Uncovering the Keystone Neurons of LLM with Just a Few Prompts

ArXi:2605.24846v1 Announce Type: cross Large language models (LLMs) display strong comprehensive abilities, yet the internal mechanisms that these behaviors remain insufficiently understood. In this work, we show that across a wide range of open-weight Transformers, a subset of neurons remains consistently highly activated during inference across tasks of multiple capability dimensions. By probing along the cross-task activation strength, an extremely sparse subset is isolated, whose removal causes a collapse in model behavior, which we term keystone neurons.