Discovering Sparse Counterfactual Factors via Latent Adjustment for Survey-based Community Intervention

ArXi:2605.04460v1 Announce Type: new Transportation surveys are widely used to understand travel preferences and adoption barriers, yet most survey-based analyses remain descriptive or predictive and rarely provide sparse, policy-feasible intervention strategies. We study sparse counterfactual community intervention from survey responses, where the goal is to shift a target respondent group toward a desired reference group through controllable survey-variable adjustments.