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> In order to predict "An" instead of “A”, you need to know that you're going to say something that starts with a vowel next. So you're incentivized to figure o
by stonemetal12 2y ago
> In order to predict "An" instead of “A”, you need to know that you're going to say something that starts with a vowel next. So you're incentivized to figure out one word ahead, and indeed, Claude realizes it's going to say astronomer and works backwards.
Is there evidence of working backwards? From a next token point of view,
predicting the token after "An" is going to heavily favor a vowel. Similarly predicting the token after "A" is going to heavily favor not a vowel.
- colah3 2y agoYes, there are two kinds of evidence. Firstly, there is behavioral evidence. This is, to me, the less compelling kind. But it's important to understand. You are of course correct that, once Cluade has said "An", it will be inclined to say something starting with a vowel. But the mystery is really why, in setups like these, Claude is much more likely to say "An" than "A" in the first place. Regardless of what the underlying mechanism is -- and you could maybe imagine ways in which it could just "pattern match" without planning here -- it is preferred because in situations like this, you need to say "An" so that "astronomer" can follow. But now we also have mechanistic evidence. If you make an attribution graph, you can literally see an astronomer feature fire, and that cause it to say "An". We didn't publish this example, but you can see a more sophisticated version of this in the poetry planning section - https://transformer-circuits.pub/2025/attribution-graphs/biology.html#dives-poems https://transformer-circuits.pub/2025/attribution-graphs/bio...
- troupo 2y ago> But the mystery is really why, in setups like these, Claude is much more likely to say "An" than "A" in the first place. Because in the training set you're likely to see "an astronomer" than a different combination of words. It's enough to run this on any other language text to see how these models often fail for any language more complex than English
- shawabawa3 2y agoYou can disprove this oversimplification with a prompt like "The word for Baker is now "Unchryt" What do you call someone that bakes? > An Unchryt" The words "An Unchryt" has clearly never come up in any training set relating to baking
- troupo 2y agoThe truth is somewhere in the middle :)
- miraculixx 2y agoAttention is all you need.
- miraculixx 2y agoOk there is correlation. But is there causation?