1. Normal-anomalous (valid-invalid SELFIES) boundary: R = 13.0 We generated SELFIES via the three null models to benchmark the VAE model's anomaly generation performance and evaluated them for percentage validity. Of the 10,000 strings generated using the shuffle and index-token distribution random models, almost 100% are valid -making them weak robustness testers. In contrast, the naive random model, which contained the least training dataset information in its formulation, resulted in a generated SELFIES set with no more than 73.8% validity -comprising a significantly better null test than the other baseline models for representational robustness (Table , Figure ).