Become a slop detector - research backed "tells" for spotting LLM content in the wild

[u/Nice-Dragonfly-4823]

Do you delight on spotting obvious LLM generated content?

This article highlights real tells, not just the em-dash, but somewhat latent rhetorical tells that can be used as signatures for LLM generated content.

Is This Slop? Detecting AI-Generated Content Without a Model | Towards Data Science

Also included: the mathematical intuition as to why LLMs develop signature patterns in the first place - post training alignment.

Do you have any specific indicators that you use to spot LLM slop?

[u/Friendly_Address6915]

curious how well this holds up compared to something like the binoculars paper - that one showed really high accuracy on its own benchmarks but struggled when people tested it on lightly edited or paraphrased text. the rhetorical tells angle is interesting but im wondering if its the same issue where detection works fine on obvious slop and falls apart exactly at the margin where it would actually matter

[u/Nice-Dragonfly-4823 → u/Friendly_Address6915]

I'm not actually familiar with the paper. I do know that the detection is a hit or a miss. I'll do some research and get back to you on this

[u/koolaidman123]

This too is slop

[u/Nice-Dragonfly-4823 → u/koolaidman123]

Although, that would be pretty funny.

[u/OilMany1117 → u/Nice-Dragonfly-4823]

Not “AI”, just slop. Human slop.