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Task-Aware QUBO Allocation for Mixed-Precision Quantization

arXiv · AI, language, vision and robotics · article · Sep 4, 2026 · UTC

Mixed-precision quantization requires discrete allocation of weight and activation bit-widths, followed by recovery of the selected network. We develop a task-aware quadratic unconstrained binary optimization (QUBO) surrogate with separate weight and activation profiles, a bit-operation (BOP) cost, and selected structural priors. QUBO provides a network-wide allocation that can be refined through direct validation-based PROTES search. On a compact NAFBlock-based denoiser, the refined route achieves 37.192 dB after LSQ+ at 4.035\% routed-layer BOPs, versus 37.092 dB at 4.101\% for a HAWQ-style

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