Alessio Fanelli: observation

Transcript context

…Yeah. But you also want humans to actually say the truth. Disagree. Yes. Exactly. To challenge you. Definitely. If what you're thinking is not factual. There was also this cool paper by Cohere and the University of Edinburgh, which was human feedback is not gold standard, I think. And where they actually established super interesting things such as humans prefer models which are over assertive. And if you have the choice between an answer which is false, but given super assertively and an answer which is right, but not as assertive, humans naturally will say the assertive but false answer is a better one. So basically, Arenas are not giving you factuality, which should be a super important aspect of LLMs, I think. That's the same with everyday life. You know, people just trust the person saying the thing assertively, even though it's false, and then actually try and figure out what the truth is. So yeah, I think you mentioned that, you know, it's like a more social experiment. I think it's a good point. Like the same biases that people have interacting with humans, they kind of put in the models themselves. Yeah, definitely. In these things. But there's also the fact that some like the judgments and the likings that we have in real life do not necessarily have the same impacts as LLMs, which are used in production, right? So you don't want the best LLM, according to everybody, to be the one which is going to be the most psychophantic and then get propaganda chatbots or something. On anything like an Arenas, there can be also the problem of the lack of diversity of the annotators, because most of the users of the chatbot arenas, for example, tend to be, from what I gathered, men from the US. I'm sorry, but this is not a diverse demographic. So those are reasons for which human evaluations, in my opinion, are quite limited.…

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