where z i is the CLM (logit) output for the i-th token, and j runs over all SMILES tokens in the vocabulary. The temperature value (T) controls the randomness of the sampling: T = 1 corresponds to standard softmax sampling with no post-hoc modification of the probabilities (multinomial sampling), T > 1 allows generating more diverse outputs, while T < 1 promotes higher-probability tokens, resulting in more deterministic and repetitive outputs. In this work, we used T= 1.0 (multinomial sampling) for CLM evaluation. For self-training augmentation, a value of T = 0.5 was used.