Marginal Response Surface Elicitation for Zero-Label Tabular Learning
Tabular learning uses structured data to predict target outcomes. Traditionally, this process has relied on labeled data. However, large language models (LLMs) can be used to elicit domain priors based on the task description and feature semantics, thereby enabling predictions without labeled data. We propose Marginal...
Liang-Yu Teng, Yi-Chen Ding, Jing Liu et al.
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