The overwhelming majority of true statements isn't in the training corpus due to a combinatorial explosion. What it means that they are more likely to occur there?
Uh, to explain what? You probably read something into what I said while I was being very literal.
If you train an LLM on mostly false statements, it will generate both known and novel falsehoods. Same for truth.
An LLM has no intrinsic concept of true or false, everything is a function of the training set. It just generates statements similar to what it has seen and higher-dimensional analogies of those .
Reasoning allows to produce statements that are more likely to be true based on statements that are known to be true. You'd need to structure your "falsehood training data" in a specific way to allow an LLM to generalize as well as with the regular data (instead of memorizing noise). And then you'll get a reasoning model which remembers false premises.
You generate your text based on a "stochastic parrot" hypothesis with no post-validation it seems.
The overwhelming majority of true statements isn't in the training corpus due to a combinatorial explosion. What it means that they are more likely to occur there?
The training set is far too small for that to explain it.
Try to explain why one shotting works.
Uh, to explain what? You probably read something into what I said while I was being very literal.
If you train an LLM on mostly false statements, it will generate both known and novel falsehoods. Same for truth.
An LLM has no intrinsic concept of true or false, everything is a function of the training set. It just generates statements similar to what it has seen and higher-dimensional analogies of those .
Reasoning allows to produce statements that are more likely to be true based on statements that are known to be true. You'd need to structure your "falsehood training data" in a specific way to allow an LLM to generalize as well as with the regular data (instead of memorizing noise). And then you'll get a reasoning model which remembers false premises.
You generate your text based on a "stochastic parrot" hypothesis with no post-validation it seems.