GenCAR: Generative Counterfactual Alignment with Risk-Controlled Selection for Out-of-Distribution Recommendation
GenCAR is proposed, which couples preference-grounded counterfactual supervision with calibrated set selection with calibrated set selection, and theoretically bound conditional counterfactual approximation error and prove finite-sample, distribution-free control of proxy-label FDR under exchangeability and positive re...