Adversarial Attacks on Tables with Entity Swap. (arXiv:2309.08650v1 [cs.CL])

Abstract:The capabilities of large language models (LLMs) have been successfully applied in the context of table representation learning. The recently proposed tabular language models have reported state-of-the-art results across various tasks for table interpretation. However, a closer look into the datasets commonly used for evaluation reveals an entity leakage from the train set into the test set. Motivated by this

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