FollowTable is the first large-scale benchmark for instruction-following table retrieval, paired with an Instruction Responsiveness Score, showing that existing models fail to adapt to fine-grained constraints beyond topical similarity.
arXiv preprint arXiv:2505.11545 (2025)
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PIPER retrieves and ranks tabular datasets by profiling their content and using LLM-generated queries for dense vector search, outperforming metadata baselines and TableQA methods in low-metadata settings.
Table representations must be permutation-invariant to preserve semantic structure, and a new header-aligned encoder moves toward this ideal while exposing fragility in existing LLM table embeddings.
citing papers explorer
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FollowTable: A Benchmark for Instruction-Following Table Retrieval
FollowTable is the first large-scale benchmark for instruction-following table retrieval, paired with an Instruction Responsiveness Score, showing that existing models fail to adapt to fine-grained constraints beyond topical similarity.
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PIPER: Content-Based Table Search via profiling and LLM-Generated Pseudoqueries
PIPER retrieves and ranks tabular datasets by profiling their content and using LLM-generated queries for dense vector search, outperforming metadata baselines and TableQA methods in low-metadata settings.
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Towards Platonic Representation for Table Reasoning: A Foundation for Permutation-Invariant Retrieval
Table representations must be permutation-invariant to preserve semantic structure, and a new header-aligned encoder moves toward this ideal while exposing fragility in existing LLM table embeddings.