Papers by Felix Steinbauer

1 papers
P-TA: Using Proximal Policy Optimization to Enhance Tabular Data Augmentation via Large Language Models (2024.findings-acl)

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Challenge: Contemporary approaches to generate tabular data are limited due to the lack of external knowledge.
Approach: They propose to use proximal policy optimization to apply GANs and fine-tune Large Language Models to enhance the probability distribution of tabular features.
Outcome: The proposed method improves accuracy of GANs and LLMs over state-of-the-art over three real-world datasets.

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