Systematic D-Wave experiments across Max-Cut, Number Partitioning, and sparse clustering show reverse annealing yields larger efficiency gains than longer forward anneals, with benefits growing for larger, more complex instances.
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A systematic literature review defines self-explainability, proposes a taxonomy and levels framework, and reports that most approaches are conceptual with no standard evaluation method.
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Extending the computational reach of Quantum Annealing using Reverse Annealing
Systematic D-Wave experiments across Max-Cut, Number Partitioning, and sparse clustering show reverse annealing yields larger efficiency gains than longer forward anneals, with benefits growing for larger, more complex instances.
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Self-Explainability in Self-Adaptive and Self-Organising Systems: Status and Research Directions
A systematic literature review defines self-explainability, proposes a taxonomy and levels framework, and reports that most approaches are conceptual with no standard evaluation method.