用大模型让可视化分析系统能听懂人话，实现自然语言交互。
LLM-Assisted Visual Analytics: Opportunities and Challenges
- 将大模型融入数据管理、交互、作图和生成全流程。
- 支持跨领域知识调用与多模态语言交互，提升分析效率。
- 适合想构建智能可视化系统的研究人员参考。
本文探讨将大语言模型（LLMs）融入视觉分析（VA）系统，通过自然语言交互提升其能力。综述了该新兴领域的研究方向，涵盖数据管理、语言交互、可视化生成及语言生成等环节。强调大模型为视觉分析带来的新可能，如构建可视化-语言联合模型，实现跨领域知识访问、多模态交互与引导式分析。同时深入讨论当前大模型在视觉分析任务中的主要挑战。本文旨在为未来从事大模型辅助视觉分析的研究者提供指导，帮助其规避常见开发障碍。
原文摘要 · Abstract (English)
We explore the integration of large language models (LLMs) into visual analytics (VA) systems to transform their capabilities through intuitive natural language interactions. We survey current research directions in this emerging field, examining how LLMs are integrated into data management, language interaction, visualisation generation, and language generation processes. We highlight the new possibilities that LLMs bring to VA, especially how they can change VA processes beyond the usual use cases. We especially highlight building new visualisation-language models, allowing access of a breadth of domain knowledge, multimodal interaction, and opportunities with guidance. Finally, we carefully consider the prominent challenges of using current LLMs in VA tasks. Our discussions in this paper aim to guide future researchers working on LLM-assisted VA systems and help them navigate common obstacles when developing these systems.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。