For example, the autonomous driving systems are usually equipped with multiple sensors to collect information from different perspectives [2]. In medical diagnosis [3], multimodal data usually come from different types of examinations, typically including a variety of clinical data.

In this paper, we study the identification of nested counterfactuals from an arbitrary combination of observations and experiments. Specifically,building onamore explicit definition ofnested counterfactuals, we prove the counterfactual unnesting theorem (CUT), which allows one to map arbitrary nested counterfactuals to unnested ones.