Research is a fundamental process driving the advancement of human civilization, yet it demands substantial time and effort from researchers. In recent years, the rapid development of artificial intelligence (AI) technologies has inspired researchers to explore how AI can accelerate and enhance research. To monitor relevant advancements, this paper presents a systematic review of the progress in this domain. Specifically, we organize the relevant studies into three main categories: hypothesis formulation, hypothesis validation, and manuscript publication. Hypothesis formulation involves knowledge synthesis and hypothesis generation. Hypothesis validation includes the verification of scientific claims, theorem proving, and experiment validation. Manuscript publication encompasses manuscript writing and the peer review process. Furthermore, we identify and discuss the current challenges faced in these areas, as well as potential future directions for research. Finally, we also offer a comprehensive overview of existing benchmarks and tools across various domains that support the integration of AI into the research process. We hope this paper serves as an introduction for beginners and fosters future research. Resources have been made publicly available at https://github.com/zkzhou126/AI-for-Research.

翻译：研究是推动人类文明进步的基本过程，但其需要研究人员投入大量时间和精力。近年来，人工智能技术的快速发展激发了研究者探索如何利用AI加速和增强研究。为追踪相关进展，本文对该领域的进展进行了系统性综述。具体而言，我们将相关研究组织为三个主要类别：假设提出、假设验证和论文发表。假设提出涉及知识综合与假设生成。假设验证包括科学主张的验证、定理证明和实验验证。论文发表涵盖稿件撰写和同行评审过程。此外，我们识别并讨论了这些领域当前面临的挑战，以及未来潜在的研究方向。最后，我们还全面概述了支持AI融入研究过程的跨领域现有基准和工具。我们希望本文能为初学者提供入门指引，并促进未来的研究。相关资源已在 https://github.com/zkzhou126/AI-for-Research 公开提供。