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Indeed and it gave several other actual citation with seemingly correct summaries. And it's definitely less prone to obvious bs than just a few weeks ago. For
by joe_the_user 4y ago
Indeed and it gave several other actual citation with seemingly correct summaries.
And it's definitely less prone to obvious bs than just a few weeks ago. For a lot of general things, it gives a summary paragraph that's seems a distillation of standard information - the main problems seem to appear when these "scripts" lack consistency.
Edit: Once it "learns" to get citations right, you'll have to dig into those to see if it's right. It's easy to see that arms not looking good.
- tsimionescu 4y ago> Once it "learns" to get citations right, you'll have to dig into those to see if it's right. It's easy to see that arms not looking good. But that's fundamentally not possible for the model as is, not in the sense you would normally think of citations at least. If it were to give an honest answer on "why did you say that Obama was born in Chicago", the model would generate training set example with propositions like Obama was born in ____, ___ was born in Chicago, ____ was ____ in ____ and so on - because that is how it learns. Instead, to generate what you would actually want as citations, it would have to have a way to look up the statement it just produced in a corpus of "citeable materials" and find the closest match, based on some entirely different ML model most likely (presumably something similar to Google's search algos).