Papers by Gilbert Badaro

1 papers
Transformers for Tabular Data Representation: A Survey of Models and Applications (2023.tacl-1)

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Challenge: Recent research efforts extend LMs by developing neural representations for structured data.
Approach: They propose to extend transformer-based language models to tabular data by analyzing inputs, model training, and supported downstream tasks.
Outcome: The proposed models are compared against existing models and are based on a traditional pipeline.

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