Almost certainly not original idea: Given the increasing fine-tuning access to models (see also the recent reinforcement fine tuning thing from OpenAI), see if fine tuning on goal directed agent tasks for a while leads to the types of scheming seen in the paper. You could maybe just fine tune on the model’s own actions when successfully solving SWE-Bench problems or something.
(I think some of the Redwood folks might have already done something similar but haven’t published it yet?)
Almost certainly not original idea: Given the increasing fine-tuning access to models (see also the recent reinforcement fine tuning thing from OpenAI), see if fine tuning on goal directed agent tasks for a while leads to the types of scheming seen in the paper. You could maybe just fine tune on the model’s own actions when successfully solving SWE-Bench problems or something.
(I think some of the Redwood folks might have already done something similar but haven’t published it yet?)