#attention-sink

1 articles

01 ·Inference & Serving·★ MEMBER·PAPER·16 min read SMELT explained (arXiv:2609.01343) — compute-matched looping Does running the same layers twice help once the budget is matched? SMELT holds per-token FLOPs, total parameters and KV cache within about 4%, loops the middle half twice, and reports 6.8-18.0% training-FLOPs savings on the compute-optimal frontier.