Wouldn't self-improvement mean that the LLM changes its neural network (i.e. the weights or layers or back propagation algorithm etc) or modify its training data?
If it's actively building the next generation of itself, I'd say that counts. It's more like a parent raising their kid well than it is like a parent modifying their own mind, but the result is still that you have a better model in a year than you do now.
