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KathDB: Explainable Multimodal Database Management System with Human-AI Collaboration

Summary: KathDB embeds foundation-model reasoning into a relational DBMS to support multimodal queries (tables, text, images, video) while preserving relational semantics and optimization. Introduces human-AI interaction at parsing, execution, and explanation for iterative, explainable results avoiding black-box LLM or manual ML-UDF workflows. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
573
Venue
CIDR
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,120 | 30.57%
DOI
-

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BibTeX Citation

@inproceedings{xiao_cidr26,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '26},
        title = {{KathDB: Explainable Multimodal Database Management System with Human-AI Collaboration}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Xiao, Guorui and Zhang, Enhao and Sullivan, Nicole and Hansen, Will and Balazinska, Magdalena},
        year = {2026}
}

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