TableCopilot: A Table Assistant Empowered by Natural Language Conditional Table Discovery
Journal:
arXiv
Published Date:
Jul 11, 2025
Abstract
The rise of LLM has enabled natural language-based table assistants, but
existing systems assume users already have a well-formed table, neglecting the
challenge of table discovery in large-scale table pools. To address this, we
introduce TableCopilot, an LLM-powered assistant for interactive, precise, and
personalized table discovery and analysis. We define a novel scenario, nlcTD,
where users provide both a natural language condition and a query table,
enabling intuitive and flexible table discovery for users of all expertise
levels. To handle this, we propose Crofuma, a cross-fusion-based approach that
learns and aggregates single-modal and cross-modal matching scores.
Experimental results show Crofuma outperforms SOTA single-input methods by at
least 12% on NDCG@5. We also release an instructional video, codebase,
datasets, and other resources on GitHub to encourage community contributions.
TableCopilot sets a new standard for interactive table assistants, making
advanced table discovery accessible and integrated.
