Large language models (LLMs) are widely used for tabular data analysis, but their performance often does not transfer from standard Table QA benchmarks to real-world settings, where tables are typically non-relational, with hierarchical headers, merged cells, inconsistent units, noise, and implicit cross-table dependen...
Michele Luca Contalbo, Matteo Paganelli, Paolo Papotti et al.· Proceedings of the 35th ACM...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.