Hamming Attention Distillation binarizes transformer keys and queries to +1/-1 and prunes attention to the top N links, reporting single-point accuracy losses and large simulated hardware savings.
The groq software-defined scale-out tensor streaming multipro- cessor: From chips-to-systems architectural overview
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Hamming Attention Distillation: Binarizing Keys and Queries for Efficient Long-Context Transformers
Hamming Attention Distillation binarizes transformer keys and queries to +1/-1 and prunes attention to the top N links, reporting single-point accuracy losses and large simulated hardware savings.