The paper introduces the ItD framework to improve the inductive capability of Large Language Models (LLMs) through deduction. It consists of two main components: Deductive Data Generation and Naive Bayesian Induction. The framework is tested on two types of induction tasks: Instruction Induction and List Function, showcasing significant performance improvements compared to existing methods. ItD effectively leverages the deductive capability of LLMs to enhance their inductive abilities.
A otro idioma
del contenido fuente
arxiv.org
Ideas clave extraídas de
by Wangtao Sun,... a las arxiv.org 03-12-2024
https://arxiv.org/pdf/2403.05789.pdfConsultas más profundas