From Tokens to Policy: Causal and Interpretable Heterogeneous Treatment Effects Identification

Excerpt

arXiv:2606.17010v2 Announce Type: replace Abstract: Heterogeneous Treatment Effect (HTE) identification is essential to explain the impact of an intervention and optimize our policies accordingly. Existing approaches trade expressivity for interpretability, but, if some active heterogeneity drivers are unmeasured, methods at both ends of this spectrum allow for spurious HTE characterization with no causal reading. In this work, we focus on controlled experiments and argue that an oracle HTE caus