7 Comments
User's avatar
TaoistHacker's avatar

Why does the system allow meaning to collapse while remaining structurally valid?

ToxSec's avatar

because the tokenizer and the training loop are two different systems that never talk to each other, essentially.

the tokenizer gets built from one corpus, picking merges based on frequency.

the embeddings get updated from a different corpus, based on gradient flow.

a slot can exist in the vocabulary and never receive a single gradient update. the vector stays at initialization noise forever.

at runtime, the forward pass doesn't care. token ID lookup succeeds.

the model just happens to be reasoning over a vector that means nothing. garbage in, fluent-sounding garbage out.

and we get strange behaviors! sometimes 1 word jailbreaks =)

TaoistHacker's avatar

I am concerned with what kind of system allows that failure to exist unnoticed and uncontained. I am asking:

Why is a system allowed to operate on meaningless inputs without any boundary, detection, or containment?

Erich Winkler's avatar

Great article! I must admit this isn’t my area of expertise, and the problem is clearly described in a way I could easily understand!

ToxSec's avatar

really appreciate that Erich! thanks a ton :)

Raghav Mehra's avatar

Wow! I've seldom thought about token-level security and tokenizer risk from this view point. Thanks Chris!

ToxSec's avatar

thanks a ton! yeah i think it’s low enough level to slide under most people’s radar!