Modern large language models - transformers and diffusion language models - are built around two canonical algorithmic tasks: prediction and generation. We prove unconditional separations between low-depth quantum computation and the corresponding bounded-resource classical language-model architectures in both regimes....
Srinivasan Arunachalam, Arkopal Dutt, H. Krovi et al.· 0 citations
Gowers, Green, Manners, and Tao (Annals'25) recently resolved Marton's polynomial Freiman-Ruzsa conjecture. We give an algorithmic counterpart to their result: given uniform sampling and membership-oracle access to a set $A \subseteq \mathbb{F}_2^n$ with doubling constant at most $K$, our algorithm outputs a subspace o...
Srinivasan Arunachalam, Arkopal Dutt, Sabee Grewal et al.· 1 citation
The results expand the range of dynamical systems that quantum computers can simulate efficiently by developing efficient algorithms for linear Volterra integro-differential equations with a convolution memory kernel that output a quantum state encoding the state description over a time interval or at a particular time...
Abtin Ameri, Arkopal Dutt, H. Krovi· 0 citations
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