Re continuous fine-tuning: how do you avoid catastrophic forgetting in your proposal?

My understanding is that this is what the LoRAs are for; my belief is that they serve as "memory" to their live observations (a more NN-like cache, say), while the main LLM remains unchanged. These LoRAs are also weighted, so that LoRAs irrelevant to the current task will not be trained, while the relevant LoRAs will be reinforced.

But I never built it, so I am not sure if such an emergent state will appear or not.