Methods › General › Deep Tabular Learning › TABBIE
TABBIE
Introduced by Hiroshi Iida et al. in TABBIE: Pretrained Representations of Tabular Data
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
TABBIE is a pretraining objective (corrupt cell detection) that learns exclusively from tabular data. Unlike other approaches, TABBIE provides embeddings of all table substructures (cells, rows, and columns). TABBIE can be seen as a table embedding model trained to detect corrupted cells, inspired by the ELECTRA objective function.
Papers archive 2025-07-28
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TABBIE: Pretrained Representations of Tabular Data 6 May 2021 · 2 repositories · arXiv:2105.02584
Tasks archive 2025-07-28
4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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