NLCO benchmark shows LLMs achieve reasonable feasibility on small natural-language CO tasks but degrade on larger instances, with set-based problems easier than graph-structured or bottleneck-objective ones.
arXiv preprint arXiv:2505.16952 (2025)
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Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization
NLCO benchmark shows LLMs achieve reasonable feasibility on small natural-language CO tasks but degrade on larger instances, with set-based problems easier than graph-structured or bottleneck-objective ones.
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Unsupervised Diffusion Solver for Combinatorial Optimization via Combinatorial Adjoint Matching
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