LATIDIA · Investigación

Grandes modelos lingüísticos (LLM)

arXiv:2610.37932v1 Tipo de anuncio: nuevo Resumen: Los modelos de lenguaje grandes (LLM) han surgido como herramientas potenciales para la optimización numérica. A pesar de los resultados prometedores, sus capacidades intrínsecas de optimización y limitación

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arXiv:2610.37932v1 Announce Type: new Abstract: Large language models (LLMs) have emerged as potential tools for numerical optimization. Despite promising results, their intrinsic optimization capabilities and limitations remain poorly understood, particularly in high dimensions. This paper investigates the ability of LLMs to exploit mathematical problem structures and generate feasible, near-optimal solutions. We develop an evaluation framework that distinguishes solution quality from execution failures, including numerical inaccuracies, constraint violations, and output-format errors. Using representative problems from convex optimization, fractional programming, and constrained projection, we assess LLM performance against deterministic reference solvers across different dimensions. Our results reveal that LLMs can capture useful optimization structures and produce near-optimal solutions, even when their outputs