Non-Gaussianity Reveals Interpretable Directions in Language Models.

arXiv:2606.11722v2 Announce Type: replace-cross Abstract: Finding human-interpretable directions in language-model activations is important for understanding and controlling model behavior. These directions are usually discovered through indirect learning obje