> LoRA works well when not capacity constrained, i.e., the number of trainable parameters exceeds the amount of information to be learned, which can be estimated in terms of dataset size

I’m shocked they didn’t look at progressive merging of LoRAs. Research shows that’s the best way of improving its ability to model higher level features.

Seems like a massive miss, not to mention there is other research that contradicts a lot of their findings. This feels a bit like a researchers first pass at learning LoRA