Talking to the person who gave it to you, in my experience.
In my own testing, Pangram is excellent at detecting the default output styles of LLMs.
If you tell the LLM to change its output style, so it’s not full of “load-bearing spaced em dashes that aren’t X, they aren’t Y. they’re Z.” constructions (which humans are pretty good at detecting on their own), the false negative rate soars.
In my own testing, Pangram is excellent at detecting the default output styles of LLMs.
If you tell the LLM to change its output style, so it’s not full of “load-bearing spaced em dashes that aren’t X, they aren’t Y. they’re Z.” constructions (which humans are pretty good at detecting on their own), the false negative rate soars.