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Re:Non-determinism in GPT-4 is caused by Sparse MoE by eru on Friday August 04, 2023 @08:59PM (#37007846)
It depends on why you want to read papers and what you want to get out of it.

https://news.ycombinator.com/item?id=37006967 suggested some avenues for finding some classic papers. The follow-up https://news.ycombinator.com/item?id=37007360 pointed out some circumstances where that's not ideal. But in the process, implicitly assumes that you want to become familiar with current research, instead of just enjoying classic papers for some other motivation.

I mostly read papers in mathematics and computer science. For other disciplines I mostly rely on pop science, like Slate Star Codex or Money Stuff and blogs. There's also The Monad Reader (https://wiki.haskell.org/The_Monad.Reader) if you are interested in functional programming.

There's various blogs with interesting articles. Eg Vitalik Buterin has great stuff, like https://vitalik.ca/general/2017/11/09/starks_part_1.html and he links to the original papers. (I have no conclusive opinions on whether crypto-currencies are useful or good for the real world, but I do find the math behind some of them endlessly fascinating. Especially zero-knowledge proofs.)

Wikipedia is also often a good starting point. Whenever you read about a random topic, Wikipedia usually has an article that comes with plenty of references. Eg https://en.wikipedia.org/wiki/Forth_Bridge#References links to http://www.bath.ac.uk/ace/uploads/StudentProjects/Bridgeconf... and down the rabbit hole you go.

https://gwern.net/ also has great write-ups and links to original papers.

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