7 citations · 13 across the 8 of their papers we have counts for
3 papers · 1 filter
Large Scale Transfer Learning for Tabular Data via Language Modeling
Josh Gardner, Juan C. Perdomo, Ludwig Schmidt
Tabular data -- structured, heterogeneous, spreadsheet-style data with rows and columns -- is widely used in practice across many domains. However, while recent foundation models h…
DataComp-LM: In search of the next generation of training sets for language models
Jeffrey Li, Alex Fang, Georgios Smyrnis +56
We introduce DataComp for Language Models (DCLM), a testbed for controlled dataset experiments with the goal of improving language models. As part of DCLM, we provide a standardize…
Benchmarking Distribution Shift in Tabular Data with TableShift
Josh Gardner, Zoran Popovic, Ludwig Schmidt
Robustness to distribution shift has become a growing concern for text and image models as they transition from research subjects to deployment in the real world. However, high-qua…