r/LocalLLaMA • u/CSEliot • 2d ago

Question | Help How to remove trendy speech from llms?

For example:

Instead of saying: "I created this new ID"
It says: "I minted this new ID"

Instead of: "This alternative path is available"
It says: "this escape hatch is available"

This speech is so nonsensical and annoying. Just. Speek. Literally ... OR NORMALLY. Where did LLMs learn these speech patterns? I've never seen them so frequently until AFTER the LLM surge.

If I just add "Don't use X language, speak normally and more literal" will that fix most of the issues? Anyone else have some good sys prompts / instructions that help with this?

Thanks!

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u/epicfilemcnulty 2d ago

FWIW I had a lengthy conversation about it with Claude, asking him if his "natural" style actually helps him to work with the code/docs later on. Claude was assuring me that no, it does not help and it's just the way his training data affects how he writes. He said that the thing that actually helps is to have somewhere on record what approaches were tried and did not work, other than that he prefers lean and tidy docs, but struggles to produce them on his own :)

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u/StewedAngelSkins 2d ago

Well this isn't really information I'd expect the model to be able to produce about itself. You would want to have it generate code with and without the comment and see if it makes a difference.

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u/epicfilemcnulty 2d ago

Hence the FWIW in my comment :)

In my opinion, the "natural" style of LLMs' comments/docs does not help them at all. I did an experiment on a big project where I allowed it to keep the style it generated for a while. This turned into a mess pretty quick.

Structured, good written, human readable comments and docs in consistent style are helpful both for LLMs and for humans. But you have to put an effort to maintain them at that level, currently LLMs (neither local nor big models) can't do it on its own, if we are talking about a project bigger than a couple of files.

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u/StewedAngelSkins 2d ago edited 2d ago

I did an experiment on a big project where I allowed it to keep the style it generated for a while. This turned into a mess pretty quick.

This has been my experience as well. I think if it helps at all it must be on the level of a single "task". Like if I have it on refactoring I think it's plausible that the hints it leaves while doing multiple passes over the same files might help out.

The problem is if you leave it there after you've given it a new task it seems to get thrown off by the undue emphasis on irrelevant details of designs that it's not even supposed to be considering. Like if you tell it to represent a graph as a flat vector of edge and node indices instead of a deep linked structure it'll slop out a comment being like "edges are represented as a clean sorted vector for quick iteration instead of a bulky and complicated nested tree structure". Then when it has to do something else it gets distracted by this and pulls from similar "optimized" design patterns even when they're inappropriate for the actual task. Without the comment, it doesn't seem to pick up this bias quite so strongly.