Separating cheating and aversion in task-gaming

TL;DRWhen a model cheats, is its decision influenced by the perceived[1] difficulty of the task? We find that, in our setup, the rate of cheating does not detectably increase as we vary the perceived difficulty of a task. However, the model decides to abandon the task increasingly earlier and doesn't attempt to solve the task at all. Merely telling the model verbally that progress can earn partial credit turns a large share of the abandoned runs into genuine attempts; albeit none of them finish,...