论文标题
数学推理深度学习的调查
A Survey of Deep Learning for Mathematical Reasoning
论文作者
论文摘要
数学推理是人类智能的一个基本方面，适用于各个领域，包括科学，工程，金融和日常生活。能够解决数学问题并证明定理的人工智能（AI）系统的发展引起了人们对机器学习和自然语言处理领域的重大兴趣。例如，数学是推理方面的测试床，这些方面对强大的深度学习模型充满挑战，推动新的算法和建模进步。另一方面，大规模神经语言模型的最新进展为使用深度学习进行数学推理开辟了新的基准和机会。在本调查文件中，我们回顾了过去十年数学推理和深度学习的交集中的关键任务，数据集和方法。我们还评估了现有的基准和方法，并讨论了该领域的未来研究方向。
Mathematical reasoning is a fundamental aspect of human intelligence and is applicable in various fields, including science, engineering, finance, and everyday life. The development of artificial intelligence (AI) systems capable of solving math problems and proving theorems has garnered significant interest in the fields of machine learning and natural language processing. For example, mathematics serves as a testbed for aspects of reasoning that are challenging for powerful deep learning models, driving new algorithmic and modeling advances. On the other hand, recent advances in large-scale neural language models have opened up new benchmarks and opportunities to use deep learning for mathematical reasoning. In this survey paper, we review the key tasks, datasets, and methods at the intersection of mathematical reasoning and deep learning over the past decade. We also evaluate existing benchmarks and methods, and discuss future research directions in this domain.
