Introduces the Query2Effect benchmark and a two-step structured-representation framework for predicting causal effect sizes from natural language queries, with reported gains from fine-tuning and better out-of-domain generalization.
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Predicting Causal Effects from Natural Language Queries using Structured Representations
Introduces the Query2Effect benchmark and a two-step structured-representation framework for predicting causal effect sizes from natural language queries, with reported gains from fine-tuning and better out-of-domain generalization.