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GATmath y GATLc: puntos de referencia integrales para evaluar los grandes modelos de lengua árabe

Safa AlBallaa1, Nora AlTwairesh1, Abdulmalik AlSalman1

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El desarrollo de grandes modelos de lengua árabe (LLM) es un desafío debido a los parámetros de referencia limitados. Los nuevos conjuntos de datos, GATmath y GATLc, ofrecen tareas de razonamiento y lenguaje a gran escala para impulsar el progreso en la IA árabe.

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Área de la Ciencia:

  • Inteligencia artificial
  • Procesamiento del lenguaje natural
  • Lingüística computacional

Sus antecedentes:

  • Los grandes modelos de lenguaje (LLM) han avanzado la IA, pero su desarrollo requiere una evaluación sólida.
  • La evaluación de las LLM árabes se ve obstaculizada por la falta de puntos de referencia y herramientas de evaluación integrales.
  • Esta escasez limita el progreso y la aplicación en el mundo real de los modelos de lengua árabe.

Objetivo del estudio:

  • Introduzca GATmath (7k preguntas) y GATLc (9k preguntas), nuevos puntos de referencia en árabe para el razonamiento multitarea y la comprensión del lenguaje.
  • Proporcionar el primer conjunto de datos de razonamiento a gran escala y completo diseñado específicamente para el idioma árabe.
  • Facilitar una evaluación rigurosa e impulsar el avance de las LLM árabes.

Principales métodos:

  • Creó dos conjuntos de datos árabes a gran escala, GATmath y GATLc, derivados de la Prueba de Aptitud General (GAT).
  • Los conjuntos de datos abarcan diversas categorías que requieren razonamiento, análisis semántico, comprensión del lenguaje y resolución de problemas matemáticos.
  • Se evaluaron siete LLM destacados en estos puntos de referencia recientemente desarrollados.

Principales resultados:

  • El LLM de mayor rendimiento logró solo un 66.9% (GATmath) y un 64.3% (GATLc) de precisión.
  • Estos resultados ponen de relieve la dificultad significativa planteada por los conjuntos de datos GATmath y GATLc.
  • Los LLM actuales de última generación demuestran limitaciones sustanciales en el razonamiento y la comprensión del idioma árabe.

Conclusiones:

  • Los conjuntos de datos GATmath y GATLc presentan un desafío considerable para los LLM árabes existentes.
  • Hay un margen sustancial de mejora en el desarrollo de modelos de lengua árabe más capaces.
  • Estos puntos de referencia son cruciales para el avance de la investigación y el desarrollo en IA árabe.