It's still incorrect to say "even frontier LLMs will still resort to sycophancy" about something like this.
Redefining sycophancy as you're attempting to do would erase the distinction between models that are trained to be sycophantic via RLHF, and models that are just responding based on what was in their pretraining corpus.
> Yes or, in other words: there's sufficient contradictory data
The idea of "contradictory data" is a projection that you're imposing. (We might even call this an hallucination.) In the model weights are just data, and different responses are elicited by different prompts depending on their relationship to to the data.
> That the contradiction is beyond the LLM's scope is part of the problem.
Well yes. But the problem is in your mind and the minds of others who think like this.
Redefining sycophancy as you're attempting to do would erase the distinction between models that are trained to be sycophantic via RLHF, and models that are just responding based on what was in their pretraining corpus.
> Yes or, in other words: there's sufficient contradictory data
The idea of "contradictory data" is a projection that you're imposing. (We might even call this an hallucination.) In the model weights are just data, and different responses are elicited by different prompts depending on their relationship to to the data.
> That the contradiction is beyond the LLM's scope is part of the problem.
Well yes. But the problem is in your mind and the minds of others who think like this.