Specializing Without Forgetting: Analyzing Knowledge Preservation in Multilingual Model Adaptation

While continual pretraining (CPT) is a practical way to extend large language models to new languages, naïve finetuning often erodes existing capabilities through catastrophic forgetting. We investigate which model layers drive this trade-off, and whether interventions at these layers can guide know