TabOrder learns unsupervised causal variable orderings and enforces them with order-constrained attention for tabular prediction and imputation under distribution shifts.
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Causal persuasion succeeds with minimal disclosure to establish a link but demands exhaustive disclosure of common causes to rule one out, creating a fundamental asymmetry.
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Learning Causal Orderings for In-Context Tabular Prediction
TabOrder learns unsupervised causal variable orderings and enforces them with order-constrained attention for tabular prediction and imputation under distribution shifts.
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Causal Persuasion
Causal persuasion succeeds with minimal disclosure to establish a link but demands exhaustive disclosure of common causes to rule one out, creating a fundamental asymmetry.