mlsanityData to 14 Oct 2026

From Large Language Models to Databases and Back: A discussion on research and education

arXiv 2306.01388 ↗First posted 2 Jun 2023cs.DBcited by 9

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Abstract (arXiv)

This discussion was conducted at a recent panel at the 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), held April 17-20, 2023 in Tianjin, China. The title of the panel was "What does LLM (ChatGPT) Bring to Data Science Research and Education? Pros and Cons". It was moderated by Lei Chen and Xiaochun Yang. The discussion raised several questions on how large language models (LLMs) and database research and education can help each other and the potential risks of LLMs.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Jun 2023.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 4; 2025: 3; 2026: 1.

9 papers.

  1. 2023Large Language Models and Knowledge Graphs: Opportunities and Challengescited by 71
  2. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 56
  3. 2024LLM-PBE: Assessing Data Privacy in Large Language Modelscited by 41
  4. 2024Large Language Models for Education: A Surveycited by 34
  5. 2024Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Toolscited by 14
  6. 2025AGRAG: Advanced Graph-based Retrieval-Augmented Generation for LLMscited by 7
  7. 2025HypoChainer: A Collaborative System Combining LLMs and Knowledge Graphs for Hypothesis-Driven Scientific Discoverycited by 1
  8. 2025Advances in Large Language Models for Medicinecited by 1
  9. 2026Revisiting the Performance of Generative Artificial Intelligence on Introductory Object-Oriented Programming Assessments: Insights from 2026cited by 0