Goodfire reads Qwen3.6 neurons directly: ablating 92.2% of weak activations raises language-model loss by only 2.9%
Goodfire studied the MLP neurons of Qwen3.6-35B-A3B directly instead of first learning a replacement feature space. Keeping only the 320 strongest router-weighted neurons per forward pass and ablating the other 92.2% raised language-model loss by 2.9%; most neurons carry one computational mode or one dominant mode, and natural-language descriptions of them can predict, simulate and drive their firing.