Tabular Data Understanding with LLMs
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The curator’s take
This survey reviews LLM and MLLM methods for table understanding, outlining a taxonomy of tabular representations and tasks. It identifies key gaps, including limited reasoning beyond retrieval, difficulties with complex or large-scale tables, and poor generalization across diverse formats.
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