If a scientist uses an LLM to write a paper with fabricated citations - that’s a crappy scientist.
AI is not the problem, laziness and negligence is. There needs to be serious social consequences to this kind of thing, otherwise we are tacitly endorsing it.
The reviewer is not a proofreader, they are checking the rigour and relevance of the work, which does not rest heavily on all of the references in a document. They are also assuming good faith.
I've always assumed peer review is similar to diff review. Where I'm willing to sign my name onto the work of others. If I approve a diff/pr and it takes down prod. It's just as much my fault, no?
> They are also assuming good faith.
I can only relate this to code review, but assuming good faith means you assume they didn't try to introduce a bug by adding this dependency. But I would should still check to make sure this new dep isn't some typosquatted package. That's the rigor I'm responsible for.
Ph.D. in neuroscience here. Programmer by trade. This is not true. Less you know about most peer revies is better.
The better peer reviews are also not this 'thorough' and no one expects reviewers to read or even check references. Unless they are citing something they are familiar with and you are using it wrong then they will likely complain. Or they find some unknown citations very relevant to their work, they will read.
I don't have a great analogy to draw here. peer review is usually a thankless and unpaid work so there is unlikely to be any motivation for fraud detection unless it somehow affects your work.
Checking references can be useful when you are not familiar with the topic (but must review the paper anyway). In many conference proceedings that I have reviewed for, many if not most citations were redacted so as to keep the author anonymous (citations to the author's prior work or that of their colleagues).
LLMs could be used to find prior work anyway, today.