Abstract: The increasing number of Internet-enabled devices has demonstrated the need to have accurate intrusion detection systems (IDSs). To address this, we adapt the structure of two-dimensional ...

TabDPT is an open-source foundation model for tabular data based on in-context learning (ICL). It is trained on real-world data and can generalize to new tasks without additional training or ...

We present TableLLM, a powerful large language model designed to handle tabular data manipulation tasks efficiently, whether they are embedded in spreadsheets or documents, meeting the demands of real ...

Abstract: Evaluating synthetic data requires careful consideration of both utility and privacy. This study analyzes 12 synthesizers across 17 tabular health datasets, providing large-scale, comparable ...