News for hackers. Stuff that matters.
Re: by UltraSane on Wednesday July 09, 2025 @11:27AM (#44511256)
I think long term LLMs should directly generate Abstract Syntax Trees. But this is hard now because all the training data is text code.
Re: by undfined on Wednesday July 09, 2025 @12:53PM (#44512272)
There's a fair amount of experimental work happening trying different parsing and resolution procedures such that the training data reflects an AST and or predicts nodes in an AST as an in-filling capability.
Re: by catfacts on Wednesday July 09, 2025 @03:51PM (#44514126)
Do you know if any such experimental work is using a special tokenizer for example in Lisp a special token for left or right parenthesis?
Re: by saurik on Wednesday July 09, 2025 @04:38PM (#44514515)
The training data is text code that can be compiled, though, so the training data can also easily be an Abstract Syntax Tree.
Re: by UltraSane on Thursday July 10, 2025 @05:31AM (#44519057)
But is anyone actually doing this?
Re: by kenjackson on Wednesday July 09, 2025 @04:57PM (#44514669)
It's possible that LLMs build ASTs internally for programming. I have no 1st hand data on this, but it would not surprise me at all.
Re: by astrange on Wednesday July 09, 2025 @07:06PM (#44515618)
LLMs don't have memory, so they can't build anything. Insofar as they produce correct results, they have implicit structures corresponding to ASTs built into their networks during training time.
Re: by kenjackson on Thursday July 10, 2025 @10:50AM (#44521744)
"LLMs don't have memory"

That's interesting. Is there research into adding memory or has it been proven that it provides no pragmatic value over any context it outputs?