experiments, SECToR provides scaffolding around the model which, while never performing any
aspect of addition, assists the language model in learning. For example, SECToR stops fine tuning
once accuracy hits a certain threshold and this threshold was not chosen by the model itself. One can
imagine using ideas from recent work, such as Toolformer, to give a language model access to tools
or API commands that allow it to fine tune itself and add datapoints to the dataset. If successful,
one could imagine a process analogous to SECToR, except that the process would consist solely of
sampling from the model and executing the generated commands with no additional assistance. If
so, one could imagine a model learning to teach itself a wide variety of concepts, including those in
which it has to self-discover the learning process, as well as the new concepts itself.
Grounding. Grounding is an area of active discussion in the research community, with many criti-
CHAIN-OF-THOUGHTREASONING IS APOLICY IMPROVEMENTOPERATOR