arXiv cs.CL
· Papers
Scaling Inherently Interpretable Language Models
arXiv:2608.07594v1 Announce Type: new Abstract: Interpretability is often treated as a tax on capability: language models are trained as opaque systems, then explained after the fact, with methods whose reliability is difficult to establish. In this work, we challenge this premise. Rather than reverse-engineering a mod