Remembering Distinct Items, Not Tokens: A Learnable Dirichlet-Process Cache Between State-Space Models and Attention

This paper proposes a learnable Dirichlet-process cache that stores only novel inputs to bridge the gap between state-space models and attention mechanisms.

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