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Prof-K: Probabilistic One-Pass Filtering for Efficient Top-k Selection
Top-k selection is a fundamental computational primitive with applications spanning databases, information retrieval, signal processing, and modern machine learning workloads, including sparse activations and attention pruning. As data sizes grow, existing approaches become inefficient: exact method
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