In recent times, the grandeur of Large Language Models (LLMs) has not only shone in the realm of natural language processing but has also cast its brilliance across a vast array of applications. This remarkable display of LLM capabilities has ignited a surge in research contributions within this domain, spanning a diverse spectrum of topics. These contributions encompass advancements in neural network architecture, context length enhancements, model alignment, training datasets, benchmarking, efficiency improvements, and more. Recent years have witnessed a dynamic synergy between academia and industry, propelling the field of LLM research to new heights. A notable milestone in this journey is the introduction of ChatGPT, a powerful AI chatbot grounded in LLMs, which has garnered widespread societal attention. The evolving technology of LLMs has begun to reshape the landscape of the entire AI community, promising a revolutionary shift in the way we create and employ AI algorithms. Given this swift-paced technical evolution, our survey embarks on a journey to encapsulate the recent strides made in the world of LLMs. Through an exploration of the background, key discoveries, and prevailing methodologies, we offer an up-to-the-minute review of the literature. By examining multiple LLM models, our paper not only presents a comprehensive overview but also charts a course that identifies existing challenges and points toward potential future research trajectories. This survey furnishes a well-rounded perspective on the current state of generative AI, shedding light on opportunities for further exploration, enhancement, and innovation.

翻译：近期，大语言模型（LLMs）的卓越表现不仅在自然语言处理领域大放异彩，还广泛辐射至众多应用场景。这种非凡的能力展示引发了该领域研究贡献的激增，研究主题横跨神经网络架构、上下文长度增强、模型对齐、训练数据集、基准测试、效率改进等多个方向。近年学术界与产业界之间的动态协同，推动了大语言模型研究达到新高度。其中里程碑事件是ChatGPT的推出——这款基于LLM的强大AI聊天机器人引发了社会广泛关注。LLM技术的持续演进已开始重塑整个人工智能领域的格局，预示着AI算法开发与应用方式的革命性转变。面对日新月异的技术发展，本综述旨在系统梳理大语言模型领域的最新进展。通过探究背景知识、关键发现及主流方法论，我们为文献提供了实时综述。通过考察多个LLM模型，本文不仅呈现全面概览，更勾勒出识别现存挑战并指明潜在未来研究方向的路线图。本综述为生成式AI的当前态势提供了多维视角，揭示进一步探索、改进与创新的机遇。