Hybrid quantum training discovers parity bases that improve accuracy 24-42% on binary tasks and recover performance on text benchmarks, with all inference remaining classical.
A variational eigenvalue solver on a photonic quantum processor
2 Pith papers cite this work. Polarity classification is still indexing.
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A decomposed variational quantum pipeline for CROP achieves higher feasibility with PUBO formulations than global QUBO by exploiting block-diagonal structure to solve single-commodity subproblems.
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Quantum Parity Representations: Learnable Basis Discovery, Encoders, and Shadow Deployment
Hybrid quantum training discovers parity bases that improve accuracy 24-42% on binary tasks and recover performance on text benchmarks, with all inference remaining classical.
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From Cables to Qubits: A Decomposed Variational Quantum Optimization Pipeline
A decomposed variational quantum pipeline for CROP achieves higher feasibility with PUBO formulations than global QUBO by exploiting block-diagonal structure to solve single-commodity subproblems.