工业视角下的大语言模型：解读挑战与前景——综述
LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Survey
AI总结：
本综述通过调查行业从业者并分析68篇论文，揭示了大语言模型在工业应用中的挑战与机遇，提出了四个研究问题并得出相关结论。
摘要：
大语言模型（LLMs）已成为驱动众多工业应用的关键要素，在广泛多样的任务中展现出非凡的多功能性与适应性。从自然语言处理、情感分析到内容生成和个性化推荐，其无与伦比的适应性促进了各行业的广泛采用。由LLMs引发的这一变革性转变，凸显了探索其应用中所伴随的潜在挑战及改进途径的必要性。本文旨在揭示并评估在工业背景下利用LLMs所固有的障碍与机遇。为此，我们开展了一项针对一组行业从业者的调查，基于收集到的见解提出了四个研究问题，并审查了68篇行业论文以回答这些问题并得出有意义的结论。我们维护着包含该领域最新论文的Github仓库。
英文摘要：
Large language models (LLMs) have become the secret ingredient driving numerous industrial applications, showcasing their remarkable versatility across a diverse spectrum of tasks. From natural language processing and sentiment analysis to content generation and personalized recommendations, their unparalleled adaptability has facilitated widespread adoption across industries. This transformative shift driven by LLMs underscores the need to explore the underlying associated challenges and avenues for enhancement in their utilization. In this paper, our objective is to unravel and evaluate the obstacles and opportunities inherent in leveraging LLMs within an industrial context. To this end, we conduct a survey involving a group of industry practitioners, develop four research questions derived from the insights gathered, and examine 68 industry papers to address these questions and derive meaningful conclusions. We maintain the Github repository with the most recent papers in the field.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
