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cs.DB2026
TEmBed-T: A Multi-Dimensional Benchmark for Table-Level Embeddings
Ayeen Poostforoushan, Liane Vogel, Carsten Binnig
Tabular data is the dominant structured-data modality, and learning table representations has become a core research direction. Table-level embeddings in particular underpin a wide…
cs.LG2026
Towards Universal Tabular Embeddings: A Benchmark Across Data Tasks
Liane Vogel, Kavitha Srinivas, Niharika D'Souza +3
Tabular foundation models aim to learn universal representations of tabular data that transfer across tasks and domains, enabling applications such as table retrieval, semantic sea…