AI RESEARCH
Large Language Model for Discrete Optimization Problems: Evaluation and Step-by-step Reasoning
arXiv CS.CL
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ArXi:2603.07733v1 Announce Type: cross This work investigated the capabilities of different models, including the Llama-3 series of models and CHATGPT, with different forms of expression in solving discrete optimization problems by testing natural language datasets. In contrast to formal datasets with a limited scope of parameters, our dataset included a variety of problem types in discrete optimization problems and featured a wide range of parameter magnitudes, including instances with large parameter sets, integrated with augmented data.