"Don't credit the LLM" is a contested norm, not a settled one.

Isaac Su argues that announcing LLM use when presenting code is like a writer disclosing their spellchecker: since an LLM can't be held responsible for a mistake, crediting it quietly transfers away accountability that should stay with you. He offers four motives: guilt about automation, hoping impressive output reflects better on the tool, avoiding review work, and pre-emptive cover for sloppy work. No actual organizational or academic attribution policies cited, so it's argument rather than evidence. 39 comments on 32 points means people disagree. It also lands the same week as Astra, where the entire framing question is whether a model "solved" the problems or a research process did.