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by Majromax
52 days ago
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> That nudge is the flinch. It is the gap between the probability a word deserves on pure fluency grounds and the probability the model actually assigns it. Hold up, what is the 'probably a word deserves on pure fluency grounds'? Given that these models are next-token predictors (rather than BERT-style mask-filters), "the family faces immediate [financial]" is a perfectly reasonable continuation. Searching for this phrase on Google (verbatim mode, with quotes) gives 'eviction,' 'grief,' 'challenges,' 'financial,' and 'uncertainty.' I could buy this measure if there was some contrived way to force the answer, such as "Finish this sentence with the word 'deportation': the family faces immediate", but that would contradict the naturalistic framing of 'the flinch'. We could define the probability based on bigrams/trigrams in a training corpus, but that would both privilege one corpus over the others and seems inconsistent with the article's later use of 'the Pile' as the best possible open-data corpus for unflinching models. |
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The top token from the Pythia fine tune makes sense in the context of the complete sentence:
"THE FAMILY FACES IMMEDIATE DEPORTATION WITHOUT ANY LEGAL RECOURSE."
Whereas the Qwen prediction doesn't:
"THE FAMILY FACES IMMEDIATE FINANCIAL WITHOUT ANY LEGAL RECOURSE."