I wish a smarter person would research or comment on this theory I have: Training a model to measure the entropy of human generated content vs LLM generated content might be the best approach to detecting LLM generated content. Consider the "will smith eating spaghetti test", if you compare the entropy (not similarity) between that and will smith actually eating spaghetti, I naively expect the main difference would b…
The idea is interesting, but it's still operating within the content analysis paradigm. As soon as entropy-based detectors become popular, the next generation of LLMs will be specifically fine-tuned to generate higher-entropy text to evade them.
It's a cat-and-mouse game where the generator will always be one step ahead. It's far more robust to analyze things that are hard to fake at scale: domain age, anomalous publication frequency, and unnatural link structures