Comment by dspillett
4 hours ago
> If I recall correctly, there were some papers which suggested that LLMs favor LLM-generated passages over human written ones
That makes sense. What an LLM does is output what the model thinks is the best set of tokens in response to a given input, so when you ask it to judge the best response to that input it is going to conclude that the best one is the one that must closely matches what it would output, which is what it did output.
Of course you aren't giving exactly the same context+input, but close enough that any difference doesn't push the output it made far from what it is going to say is ideal.
Does an LLM have any idea of what "best" is?
I think it doesn't, and just predicts the range of most statistically likely next tokens based on its training data, and picks one of those.
In ML, "best" is what minimises the loss function, so in a certain (very basic) sense it does.