Web research and practices have evolved significantly over time, offering users diverse and accessible solutions across a wide range of tasks. While advanced concepts such as Web 4.0 have emerged from mature technologies, the introduction of large language models (LLMs) has profoundly influenced both the field and its applications. This wave of LLMs has permeated science and technology so deeply that no area remains untouched. Consequently, LLMs are reshaping web research and development, transforming traditional pipelines into generative solutions for tasks like information retrieval, question answering, recommendation systems, and web analytics. They have also enabled new applications such as web-based summarization and educational tools. This survey explores recent advances in the impact of LLMs-particularly through the use of retrieval-augmented generation (RAG)-on web research and industry. It discusses key developments, open challenges, and future directions for enhancing web solutions with LLMs.

翻译：网络研究与实践历经显著演进，为用户提供了覆盖广泛任务的多样化且易获取的解决方案。尽管Web 4.0等先进概念已从成熟技术中涌现，但大语言模型的引入深刻影响了该领域及其应用。这股LLM浪潮已如此深入地渗透至科学技术之中，以至于无一领域能置身事外。因此，LLM正在重塑网络研究与开发，将传统流水线转化为信息检索、问答系统、推荐系统和网络分析等任务的生成式解决方案。它们还催生了基于网络的摘要生成和教育工具等新型应用。本综述探讨了LLM（特别是通过检索增强生成技术的运用）对网络研究与产业影响的最新进展，讨论了利用LLM增强网络解决方案的关键发展、开放挑战及未来方向。