hmm, assuming that this article is part written by claude and part human-written, can anyone help me find a rule of thumb for "how to know if the article is worth reading"?
Because on the one hand, the prose and the presentation is painful (narrating irrelevant points, nonlinear X-axes, ambiguous chart labels, etc etc),
But on the other hand, the result that I'm assuming the author means ("on these evals, generation quality seems fairly good") is worthwhile?
Because I really struggle with this question at the moment. Am I allowed to draw an adverse inference that "if the writeup presents irrelevant text side by side with the data, then this may be a sign that the author does not understand the task that they are attempting to write up"?
I think the advice is the same regardless of AI use: read articles written by authors that have a history of high quality writing.
IMO, whether or not an LLM was used in the writing process doesn't really matter and I think it's a bit annoying that articles are being dismissed out of hand because of that.
The line is "Is this an interesting and accurate article that concisely makes it's case".
LLMs love to burn paragraphs writing about nothing which is why it's generally poor writing. Humans can do the same thing if they are trying to make very little information feel more substantial.
I say, stop trying to determine if an LLM was used and start judging based on your subjective measure that you'd have used before LLMs became widespread.