UCLA finds hybrid-attention layer ordering shapes multilinguality — alternative orders learn 2.5X faster
UCLA · hf · 2026-10-07
UCLA presents the first study of how hybrid attention affects LLM multilinguality. Interpretability analysis confirms recurrent-state inductive biases alter linguistic processing: cross-lingual representation patterns track the ordering of recurrent vs full-attention layers, with a pronounced alignment spike near the first full-attention layer. In distillation experiments, all alternative layer orderings beat the standard throughout training, learning up to 2.5X faster — suggesting multilingual models should start with a full-attention layer.
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