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by canjobear
2157 days ago
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> If you instead produce a list of sentences with similar log probabilities you will see that it contains a mix of grammatical and ungrammatical utterances. Yes, Chomsky mentions this in a footnote. But as far as I know, it hasn't been tried with modern language models. There's been some interesting work that tries to reproduce grammaticality judgments in terms of language model probability after controlling for length and lexical content. It turns out it works pretty well. For instance https://arxiv.org/pdf/1910.14659.pdf |
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> "... a structural analysis cannot be understood as a schematic summary developed by sharpening the blurred edges in the full statistical picture. If we rank the sequences of a given length in order of statistical approximation to English, we will find both grammatical and ungrammatical sequences scattered throughout the list; there appears to be no particular relation between order of approximation and grammaticalness. Despite the undeniable interest and importance of semantic and statistical studies of language, they appear to have no direct relevance to the problem of determining or characterizing the set of grammatical utterances. I think that we are forced to conclude that grammar is autonomous and independent of meaning, and that probabilistic models give no particular insight into some of the basic problems of syntactic structure."
I do think it's an important point for people to recognize. Scientific theories don't arise on their own out of large-scale statistical analyses. There is a lot of faith being put in deep learning methods these days, which are great for prediction, but not inference.