Quantum walks sound abstract, but they sit at the center of a very concrete race: who will harness quantum mechanics to solve ...

Flexible position encoding helps LLMs follow complex instructions and shifting states by Lauren Hinkel, Massachusetts Institute of Technology edited by Lisa Lock, reviewed by Robert Egan Editors' ...

Autograph first extracts loops and builds dependency graphs capturing instruction semantics and data flow, which are then converted into embeddings by Graph Neural Network. These embeddings are then ...

Abstract: With the integration of graph structure representation and self-attention mechanism, the graph Transformer (GT) demonstrates remarkable effectiveness in hyperspectral image (HSI) ...

We invite you to become contributors! Current deep learning models heavily depend on manual kernel optimizations that tightly bind model algorithms and compiler implementations to specific hardware, ...

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But the field has seen significant progress in recent years, culminating in a landmark result from Google’s quantum computing team last December. The company unveiled a new quantum processor called ...