Scholarlink

<p>Currently, the use of GenAI is the dominant topic in computer science and society. Consequently, research is momentarily underway in many areas of database technology to explore the possibilities offered by LLMs and how they can complement existing systems. However, the lack of reliability and reproducibility is a&#xa0;well-known problem. So what could be more natural than to discuss this topic at a&#xa0;conference? The Spring Symposium of the GI Specialist Group Database Systems placed this question at the center of its agenda and took place under the title <b>Can We Trust the Model? Reproducibility and Reliability of LLM Results</b>.</p><p>The two-day symposium brought together researchers from academia and industry to discuss current developments at the intersection of database systems and artificial intelligence. The scientific program featured thirteen invited talks covering topics such as LLM-assisted database technologies, knowledge graphs, information retrieval, data quality, and database education in the era of generative AI. Complementing the main program, a&#xa0;poster session provided young researchers with the opportunity to present and discuss their work with the community. The symposium was further enriched by updates from the GI Specialist Group Database Systems, an introduction to the recently founded Faculty for Informatics and Data Science at the University of Regensburg, and a&#xa0;conference dinner sponsored by Snowflake that fostered networking and scientific exchange beyond the formal program.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spring Symposium of the GI Specialist Group On Database Systems, March 4–5, 2026, Regensburg

  • 期刊论文

  • 发表日期：

    2026年7月22日

查看全文
  • Meike Klettke,
  • Tanja Auge,
  • Dominique Hausler

摘要

Currently, the use of GenAI is the dominant topic in computer science and society. Consequently, research is momentarily underway in many areas of database technology to explore the possibilities offered by LLMs and how they can complement existing systems. However, the lack of reliability and reproducibility is a well-known problem. So what could be more natural than to discuss this topic at a conference? The Spring Symposium of the GI Specialist Group Database Systems placed this question at the center of its agenda and took place under the title Can We Trust the Model? Reproducibility and Reliability of LLM Results.

The two-day symposium brought together researchers from academia and industry to discuss current developments at the intersection of database systems and artificial intelligence. The scientific program featured thirteen invited talks covering topics such as LLM-assisted database technologies, knowledge graphs, information retrieval, data quality, and database education in the era of generative AI. Complementing the main program, a poster session provided young researchers with the opportunity to present and discuss their work with the community. The symposium was further enriched by updates from the GI Specialist Group Database Systems, an introduction to the recently founded Faculty for Informatics and Data Science at the University of Regensburg, and a conference dinner sponsored by Snowflake that fostered networking and scientific exchange beyond the formal program.