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Persona vectors: Monitoring and controlling character traits in language models

anthropic.com

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Re: Persona vectors: Monitoring and controlling character traits in language models

#61
I am far from being a Mathematician, but can't AI shop create an acceptable control model and then measure the cosine distance between the current model and the control model?

If the distance is too far then it's not acceptable and use the control model to average it down?

Also, isn't this similar technique as managing hallucination? (If you have an acceptable control/baseline)

Then again, I am not a Mathmetician so I don't know the details.

Re: Persona vectors: Monitoring and controlling character traits in language models

#64

> Other personality changes are subtler but still unsettling, like when models start sucking up to users or making up facts. My understanding is that the former (sucking up) is a personality trait, substantially influenced by the desire to facilitate engagement. The latter (making up facts), I do not think is correct to ascribe to a personality trait (like compulsive liar); instead, it is because the fitness function…

Regarding truth telling, there seems to be some evidence that LLMs at least sometimes "know" when they are lying:

https://arxiv.org/abs/2310.06824

Re: Persona vectors: Monitoring and controlling character traits in language models

#67
post #51

Earlier quoted context omitted.

You mean I don't think this is automatically correct. Otherwise it very likely is correct. Either way, you're guessing the manual curation is done in a way that is favorable to include I don't know answers. Which it most likely doesn't.

its completely in the incentive to include such examples in RLHF. or you have come up with a way to increase performance that the very employees haven't. why do you think they didn't try it?

How do you know which question should be answered with 'I dont know?'. There are obvious questions which have no answer, but if only those are in the dataset, the model will answer I dont know only for unreasonable questions.

To train this effectively you would need a dataset of questions which you know the model doesn't know. But if you have that... why not answer the question and put in the dataset so that the model will know ?

That's a bit imprecise, but I think it capture the idea of why 'I don't know' answers are harder to train.

Re: Persona vectors: Monitoring and controlling character traits in language models

#68

Isn't this just control vectors rediscovered? https://www.lesswrong.com/posts/Bf3ryxiM6Gff2zamw/control-ve...

I've been referring to apparently this as "whatever a control vector is called in 2025" since they started doing it to dilute tokens under load: https://news.ycombinator.com/item?id=44082733

Re: Persona vectors: Monitoring and controlling character traits in language models

#69

> Other personality changes are subtler but still unsettling, like when models start sucking up to users or making up facts. My understanding is that the former (sucking up) is a personality trait, substantially influenced by the desire to facilitate engagement. The latter (making up facts), I do not think is correct to ascribe to a personality trait (like compulsive liar); instead, it is because the fitness function…

Furthermore, it is very rare to have the following kind of text present in the training data: "What is the answer to X?" - "I don't know, I am not sure." In this situation very often there won't be _any_ answer, plenty of difficult questions go unanswered on the internet. Yet the model probably does not interpret this scenario as such

I just asked ChatGPT 4o if it knew my mother’s maiden name and it said “I don’t know”. Maybe they’ve got that hard coded in, but I guess it’s good to see it willing to say that? Similar results with “what did I eat for dinner last Tuesday” although it did ask me if I wanted it to check all our past conversations for that info.

Re: Persona vectors: Monitoring and controlling character traits in language models

#70

> In 2023, Microsoft's Bing chatbot famously adopted an alter-ego called "Sydney,” which declared love for users and made threats of blackmail. More recently, xAI’s Grok chatbot would for a brief period sometimes identify as “MechaHitler” and make antisemitic comments. Other personality changes are subtler but still unsettling, like when models start sucking up to users or making up facts. Funny that they managed to…

What bad behaviour of Claude was as famous as Sydney, or MechaHitler, or GPT' sycophancy? I've not heard anything.
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