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Arxiv
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Fast and Simplex: 2-Simplicial Attention in Triton
- A new study explores the concept of 2-simplicial attention in Triton as a means to improve token efficiency in models.
- The research examines how the 2-simplicial Transformer architecture, which uses trilinear functions through an efficient Triton kernel implementation, can outperform traditional Transformers in tasks related to mathematics, coding, reasoning, and logic within a fixed token budget.
- The study suggests that the 2-simplicial Transformer changes the scaling laws for knowledge and reasoning tasks when compared to dot product attention, showcasing better token efficiency.
- The findings emphasize the importance of designing architectures that prioritize token efficiency, especially as large language models rely on massive internet-scale datasets.
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