In practice, sadly, developing a true ELM is currently too expensive for us to pursue (but if you want to fund us to do that, lmk). So instead, in our internal research, we focus on finetuning over pretraining. Our goal is to be able to teach a model a set of facts/constraints/instructions and be able to predict how it will generalize from them, and ensure it doesn’t learn unwanted facts (such as learning human psychology from programmer comments, or general hallucinations).
This has reminded me to revisit some work I was doing a couple of months ago on unsupervised unlearning. I could almost get Gemma-2-2B to forget who Michael Jordan was without needing to know any facts about him (other than that “Michael Jordan” was the target name)
This has reminded me to revisit some work I was doing a couple of months ago on unsupervised unlearning. I could almost get Gemma-2-2B to forget who Michael Jordan was without needing to know any facts about him (other than that “Michael Jordan” was the target name)