A unified, pre-converted, ready-to-benchmark collection of
Combinatorial-Optimization (CO) instances for discrete samplers,
annealers, and learning-based solvers. Every family referenced in the
PQQA paper Ichikawa & Iwashita, 2024
is reproduced here, together with a few broadly used community
benchmarks (G-set, DIMACS COLOR, Edwards-Anderson). The dataset is
designed to be solver-agnostic — a companion Python loader is
shipped in… See the full description on the dataset page:
https://huggingface.co/datasets/Yuma-Ichikawa/qqa4co-bench.
