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Incorporating LLM Priors into Tabular Learners
We present a method to integrate Large Language Models (LLMs) and traditional tabular data classification techniques, addressing LLMs challenges like data serialization sensitivity and biases.
Tabular Few-Shot Generalization Across Heterogeneous Feature Spaces
Despite the prevalence of tabular datasets, few-shot learning remains under-explored within this domain.
Modular Neural Ordinary Differential Equations
The laws of physics have been written in the language of dif-ferential equations for centuries.
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