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sebzim4500 t1_jdzczty wrote

Reply to comment by gunbladezero in [P] two copies of gpt-3.5 (one playing as the oracle, and another as the guesser) performs poorly on the game of 20 Questions (68/1823). by evanthebouncy

I think you're forcing the model to waste the lower layers on each step decoding that base64 string. Let it output the word normally, and you would probably see much better performance. Just don't look at the first output, if you want to still play it like a game.

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gunbladezero t1_je0yqmy wrote

Interesting. It also seems to have spelled her name wrong in BASE64 so that might be a problem. What do you mean by ‘waste the lower layers’?

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sebzim4500 t1_je16h58 wrote

I'm going to simplify a bit here, if you want a more complete answer I can write something up. I was planning on writing a blog post about this, because it is relevant to why ChatGPT does so much better when asked to show its working.

Basically, LLMs do not have any memory except what you see in the output. You may think that the network just needs to decode the base64 once and then use it to answer all the questions, but in actuality it needs to do it for every single token.

This is compounded by the fact that decoding base64 like this is a per-character operation, which GPT-n is especially bad at due to their choice of tokens. Since it only can use a finite amount of computation per token, wasting computation in this way will decrease the effectiveness.

Here's an example where simply making GPT-4 reverse the string makes it completely unable to do a straightforward calculation, unless you let it show its working.

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gunbladezero t1_je1u5ev wrote

Very interesting, thank you! I hadn't thought of that- it has to translate it for every token, you say, not just every answer? I wonder if it would work better or worse asking it to encode it in arabic, or chinese etc. Of course, it would be simple to script something to hide the answer from the player without revealing it. I do know that if it doesn't store the answer, it will completely invent one every with each question...

edit: It does work better with plaintext. Not sure if I would have guessed her but it answered the questions correctly this time.

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