They cannot “figure” it, they could learn it but for that it would need to be in it's training data (which isn't because nobody is writing down the actual pairing in every byte pair encoding in plain text. Also the LLM has no clue about what encoding it uses unless you tell it somehow in the fine-tuning process or the prompt.)
It's as feasible as telling how many chars in html lead to this comment by looking at a screenshot. LLM doesn't see characters, tokens, numbers or its own activations. LLM is a "set of rules" component in a chinese room scenario. Anything an operator of that room does is lower-level.
GGP's idea suggests that an LLM, allegedly as a whole-room, receives something like: "hey, look at these tokens: <tokens>, please infer the continuation". This puts it into a nested-room's-operator position, which (1) it is not, (2) there's no nested room.