A new functional S vanishes precisely on free line arrangements and enables discovery of verified free examples for every admissible exponent pair with up to 20 lines.
In: Proceedings of the 31st International Conference on Neural Information Processing Systems
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QARMA applies transformer-augmented reinforcement learning to qubit allocation and reuse in modular quantum systems, reporting up to 86% average reduction in inter-core communications versus optimized Qiskit baselines.
Introduces a taxonomy of nine LLM code smells, a static detection tool, and reports 73.5% prevalence with 91.3% precision and 71.8% recall across 692 projects.
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A semicontinuous relaxation of Saito's criterion and freeness as angular minimization
A new functional S vanishes precisely on free line arrangements and enables discovery of verified free examples for every admissible exponent pair with up to 20 lines.
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Learning-Optimized Qubit Mapping and Reuse to Minimize Inter-Core Communication in Modular Quantum Architectures
QARMA applies transformer-augmented reinforcement learning to qubit allocation and reuse in modular quantum systems, reporting up to 86% average reduction in inter-core communications versus optimized Qiskit baselines.
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LLM Code Smells: A Taxonomy and Detection Approach
Introduces a taxonomy of nine LLM code smells, a static detection tool, and reports 73.5% prevalence with 91.3% precision and 71.8% recall across 692 projects.