DEVLOG #13 - Context can look like learning when it is not

SL-LLM-R needs to separate temporary memory from actual model learning. A model can answer better simply because the correct information is still in its context window, even though its weights never changed. I keep those two kinds of improvement separate so short-term memory does not get reported as permanent learning.