TuniQ uses RL with a dual-encoder, shaped rewards, and action masking to autotune quantum compilation passes, improving fidelity and speed over Qiskit while generalizing across backends and scaling to large circuits.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
HPA dynamically selects agent decision orders in Stackelberg games to improve equilibria and performance in multi-agent MuJoCo control tasks.
citing papers explorer
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TuniQ: Autotuning Compilation Passes for Quantum Workloads at Scale for Effectiveness and Efficiency
TuniQ uses RL with a dual-encoder, shaped rewards, and action masking to autotune quantum compilation passes, improving fidelity and speed over Qiskit while generalizing across backends and scaling to large circuits.
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Rethinking Priority Scheduling for Sequential Multi-Agent Decision Making in Stackelberg Games
HPA dynamically selects agent decision orders in Stackelberg games to improve equilibria and performance in multi-agent MuJoCo control tasks.