The LLM doesn’t have to innately implement filtering. You can use a more traditional and concrete filtering strategy on top. So you sneak something problematic by in the prompt and it’s too clever to be caught by the input filter, but then on the output the filter can catch that the prompt tricked the LLM into generating something undesired. Another comment specified they tried this and it started to work but then suddenly it seemingly shut out the reply in the middle, presumably the minute the LLM spit something at a more traditional filter and that shut it down.
I think I’ve seen this sort of approach has been applied to largely mask embarassing answers that become memes, or to detect input known not to work, and to shut it down or redirect it to a better facility (e.g. redirecting math to wolfram alpha).
kautau@lemmy.world 5 weeks ago
It’s probably deepseek r1, which is a “reasoning” model so basically it has sub-models doing things like running computation while the “supervisor” part of the model “talks to them” and relays back the approach. Trying to imitate the way humans think. That being said, models are getting “agentic” meaning they have the ability to run software tools against what you send them, and while it’s obviously being super hyped up by all the tech bro accellerationists, it is likely where LLMs and the like are headed, for better or for worse.
GissaMittJobb@lemmy.ml 5 weeks ago
Still, this does not quite address the issue of tokenization making it difficult for most models to accurately distinguish between the hexadecimals here.
Having the model write code to solve an issue and then ask it to execute it is an established technique to circumvent this issue, but all of the model interfaces I know of with this capability are very explicit about when they are making use of this tool.
morrowind@lemmy.ml 5 weeks ago
Not really a concern. It’s basically translation, which language models excel at. It just needs a mapping of the hex to byte
GissaMittJobb@lemmy.ml 5 weeks ago
It is a concern.
Check out tiktokenizer.vercel.app/?model=deepseek-ai%2FDeep… and try entering some freeform hexadecimal data - you’ll notice that it does not cleanly segment the hexadecimal numbers into individual tokens.