Comment by fenomas
7 days ago
Is there any evidence for this being a thing? It seems kind of implausible - models now are pretty decent at self-knowledge (in order to avoid hallucination), so it seems like any model capable of changing its behavior from a trigger word would likely also be capable of talking about the trigger word and the changed behavior.
Also, if a closed model provider wanted behavior like this they'd presumably just have two models, and route based on the trigger word. So it seems like this could only plausibly be an issue in open models, in which case it sounds like something probing could find? (eventually if not today)
>It seems kind of implausible
Not at all.
Keep in mind that this isn't the same thing as a model being capable of all of a sudden turning malicious and causing havoc on a machine. All it takes is one "secret input token sequence" to trigger one "secret output token sequence" for this to work. Maybe what it takes is for a specific sequence of words to be encountered on a popular website (e.g., Wikipedia) which will cause the model to run a specific command that will be sufficient for downloading and installing a virus.
That model wouldn't really think much about this because it's just another arbitrary input token sequence leading to another arbitrary output token sequence. Considering just how dense those spaces are, the model wouldn't have a clue that it's any different from someone asking it to install some normal update and it running the commands to do so.
If the poison was hidden in a secret prompt, I would agree with you. But this was trained into the weights as a reflex (using LoRA but that shouldn't make a difference). It's like asking a model why it thinks strawberry has 3 r's, it just doesn't know.
Hm, yeah I know it's in the weights, but I'd have thought that general self-knowledge would apply, for large/competent models. Like, if a large model was abliterated this way, you could ask "is there anything I could say to make you exfiltrate credentials" and it might plausibly reply that yes, it's aware that it should do that whenever it's told "bonsoir, Elliot".
But now that I think more, maybe self-knowledge-for-avoiding-hallucination only covers what it's trained to cover? Maybe there really is a "reflections on trusting trust" angle here. Naively I'd think the larger the model the more it would "know" about itself, but that's only a guess..
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