Perhaps Dogme 95/Dogma 25 films are in a genre of their own, but they're not "genre movies." People make the same argument with "literary fiction"/"non-genre fiction" vs "genre fiction." The terms have meaning whether or not you want to acknowledge it.
Dogme is more of a methodology than genre. Genre usually means settings and tropes, like scifi or horror or superhero.
Though I’d argue that rom-com, period pieces, and biopics also are “genre”, at least to the extent a particular movie just paints by numbers within those styles.
There's actually Street View images, so you can take a look, also at the agricultural plots southwest of the town (see https://en.wikipedia.org/wiki/Potato_Patches ). There's some sheep, cattle and (I think) donkeys as well.
> Seriously? You can't fathom an honest researcher asking for AI to find a citation they know exists, and the AI inserting or modifying a citation incorrectly without them realizing?
Indeed I cannot. If you do that, you are not, in fact, an honest researcher. You're a lazy hack.
> You’re right that a single hallucinated line is not evidence of reckless disregard
It absolutely is.
> - because that could have happened on a final follow-up pass after you had performed due diligence.
A "final follow-up pass" that lets the LLM make whatever changes it deems appropriate completely negates all the due diligence you did before, unless you very carefully review the diffs. And a new or substantially changed citation should stand out in that diff so much that there's no possible excuse to missing it.
> It’s happened to me.
Then you were guilty of reckless disregard.
> I know how challenging it can be to keep bad patterns out of LLM generated output
If your research paper contains any LLM generated output you did not manually vet, you are a hack and should not get published.
Context matters a lot. I didn’t publish any papers, and didn’t even provide the context of the LLM mistakes I caught to later report on, so no, I was not guilty of reckless disregard. I found those mistakes on an acceptable timeline.
I'm not sure the concepts of accidental vs. essential complexity really applies here. Is it really "accidental complexity" that is being removed when the result is harder to understand and less practically usable?
"Essential" here means something that cannot, in any way, be further removed from consideration. In this view, things that simplify the understanding and make the program more practical are not essential - they are add-ons on top of the most primitive computational model(s). You can drastically simplify the reading of the lambda calculus by giving it direct support for integers, for example - however, you now polluted the model with an additional element that you need to describe and always keep in mind. Using Church encoding lets you get integers without introducing any new elements to the model, keeping the model simpler - but yes, the implementations of programs within that model will get much more complex to read.
Yes, I get that. I just don't think that interpretation is a good fit for the concept, since that was formulated from the POV of practical usability and cognitive load.
Though... now that I think about it, maybe it does fit - it's all about the question "practical usability for what?"
I suppose that if what you actually want to do is model and reason about theoretical computability, then most things that make languages convenient to implement things in actually are accidental complexity!
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