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Logic and the 2-Simplicial Transformer
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Logic and the 2-Simplicial Transformer
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We introduce the $2$-simplicial Transformer, an extension of the Transformer which includes a form of higher-dimensional attention generalising the dot-product attention, and uses this attention to update entity representations with tensor products of value vectors. We show that this architecture is a useful inductive bias for logical reasoning in the context of deep reinforcement learning.
Forward citations
Cited by 3 Pith papers
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