All implementations used Meditron as the backbone model, known for its performance on L+M-24. For alignment fine-tuning experiments, we initialised Meditron crossmodals, trained for molecule generation . For the model merging experiments, we combined Meditron weights trained on MoCG tasks in a 19:1 ratio. This ratio aimed to preserve the balance of information between the linguistic and molecule modalities. All models were fine-tuned using QLoRA .