interesting thank you. intuitively, prompting like this to get an answer seems basically like the first part of a fine tuning process (more exemplars). what i

interesting thank you. intuitively, prompting like this to get an answer seems basically like the first part of a fine tuning process (more exemplars). what is your thought here behind why reinforcing good output via a loss optimization is worse than the one shot example? does the model start to over fit at some point towards some local minima? and this is avoided in this scenario?