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cs.LG2026
FlexTab: A Flexible Encoder-Decoder Architecture for In-Context Learning Across Diverse Tabular Tasks
Marek Polewczyk, Maximilian Schambach, Marco Spinaci +2
We introduce FlexTab, a flexible encoder-decoder architecture for in-context learning on tabular data that pairs a single, task-agnostic encoder with a suite of task-specific decod…
cs.LG2026
Exploring Differences Between Tabular Enterprise Data and Public Benchmarks
Myung Jun Kim, Maximilian Schambach, Frank Essenberger +2
Tabular data dominate the landscape of data science, increasingly attracting innovative machine learning models and tailored benchmarks. Yet, little is known for enterprise data, w…