QnRL is a distributional quantum RL framework that distills conditional action policies from moments of quantum generative models in Hilbert space via the QuAK algorithm, reporting higher scores and fewer parameters than baselines.
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quant-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A training-free quantum generative paradigm is proposed that encodes target distributions as ground states of constructed local parent Hamiltonians for image and text generation.
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QnRL: Quantum-Native Reinforcement Learning
QnRL is a distributional quantum RL framework that distills conditional action policies from moments of quantum generative models in Hilbert space via the QuAK algorithm, reporting higher scores and fewer parameters than baselines.
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Training-Free Quantum Generative Paradigm via Local Parent Hamiltonians
A training-free quantum generative paradigm is proposed that encodes target distributions as ground states of constructed local parent Hamiltonians for image and text generation.