In this study, we delve into the challenges presented by Langer et al. who investigated that stakeholders of ML models desire XAI methods to produce human-understandable and consistent interpretations. We focus on the robustness of local XAI methods for molecular representations, specifically by comparing importance assigned to equivalent SMILES representations. Our study has broad implications for the XAI field, given the potential impact of varying importance assignments in toxicity prediction. Our contributions can be summarized as follows: