In this work, we exploit approximate, scalable, linear constraint relaxation methods (Weng et al., 2018a; Zhang et al., 2018; Wong and Kolter, 2018), which do not assume Lipschitz continuity.
we adapt the CNNCert tool (Boopathy et al., 2019) and its recurrent extension POPQORN (Ko et al., 2019) to compute robustness guarantees for text classification in the NLP domain.