arXiv cs.CLPaper
Language Models Can Control Their Own Attention
This is a real efficiency win for long-context inference. Instead of scanning the full KV cache at each step, the model declares which region it needs (global, focused, or local), and the inference engine skips the rest. It's intrinsic rather than extrinsic: the model already knows what matters. If you're running long-context inference at scale, this cuts compute per token without architectural changes. Likely to land in production systems within months.