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Geometric knowledge spaces, Attention pairing and Architectures

Xu, Shang
arXiv (All) · Papers
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68t05algebraic-geometrygeneral-topologymachine-learning
In this paper, we propose a geometric approach to deriving attention mechanisms and exploring potential new transformer architectures. We begin by formalizing the notions of knowledge worlds and attention pairings, then demonstrate how this framework naturally leads to the architectures of standard
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