I need to read the paper but I would add that 2-shot is essential how I’ve been getting GPT-3.5 to behave in my Self-INSTRUCT stuff. I use GPT-4 to generate an example that I feed into 3.5 and it definitely improves 3.5s reasoning moving forward
You may not find all that much there. It’s a pretty expensive prompt if you don’t need TOM capability. I’m always looking to understand, from a TOM perspective about LLMs themselves, where their limitations are.
Here’s another paper I just stumbled on. Long, but probably a must read. Eric Horvitz is chief scientific officer (or something like that) at Microsoft research, and a very smart guy. Acknowledgement - I followed a link in another topic about prompts, @mstefanec found it before me.
Sparks of Artificial General Intelligence: Early experiments with GPT-4
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Yeah, that’s a classic at this point. Really great paper, must read.
Maybe start a new thread (I’ll contribute!) though to track generic great papers as it’s somewhat off topic to this one.
Good idea, what should we call it? (the new thread?)
Good question, I like asking GPT4 for advice on these things
Maybe “must read GPT/LLM papers”? heh
works for me.
I’ll repost that link to start the thread
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forums rejected the title! must be at least 25 chars 
I added a ‘Foundational’ up front
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For anyone looking for this it’s here - Foundational must read GPT/LLM papers
If you post a paper in another thread that works well in the foundational one, link back so people find it 
It’s a little hidden away in the ChatGPT category which is muted for everyone I think. Not necessarily a bad thing
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Didn’t realize that! it was the closest category I could find, no way I could find to create a new category. Maybe I can still edit the original post if there is a better category you can suggest.
The community category would probably be good. It’s below the fold, but I think it’s most appropriate.
FYI the API needs you to send the entire session history each time you want a response, as they don’t retain any state on their end. So conversations get exponentially more expensive as they go on, as this history counts towards token costs each time.