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Integer linear programming (ILP) plays a pivotal role in combinatorial optimization, with applications ranging from logistics to scheduling. Recently, unsupervised learning has emerged as a promising paradigm for solving ILPs without costly labeled solutions. However, existing methods often converge prematurely to pola...
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