Multistability of Self-Attention Dynamics in Transformers
NeutralArtificial Intelligence
The paper titled 'Multistability of Self-Attention Dynamics in Transformers' explores a continuous-time multiagent model of self-attention mechanisms in transformers. It establishes a connection between self-attention dynamics and a multiagent version of the Oja flow, which computes the principal eigenvector of a matrix related to the value matrix in transformers. The study classifies the equilibria of the single-head self-attention system into four categories: consensus, bipartite consensus, clustering, and polygonal equilibria, noting that multiple stable equilibria can coexist.
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