I’m surprised at the current sentiment in the comments. Pangram is amazing and has really interesting engineering too. I would have guessed that reliably identifying LLM generated text was not possible without watermarks.
People expect a binary response, is it AI generated yes or no. But it's more complicated than that. For example, if you see an emdash, it's probably AI generated. But it can also mean the author used it for fixing grammar or tenses. LLMs can't help but try to help. The same for it's not X, but Y. Sure it's a known pattern, but it's not like people don't use this trope all the time.
In my experience, Pangram is great for detecting an author who is trying to pass someone else's work as theirs, or if they are tackling a subject they have little to no knowledge in.
How accurate is this? I want to see a negative before i provide you with a positive.
Negative? What?
I detect Claude.
Interestingly checking good chunks of their site, it detects as 100% human
I detect SPAM.
I’m surprised at the current sentiment in the comments. Pangram is amazing and has really interesting engineering too. I would have guessed that reliably identifying LLM generated text was not possible without watermarks.
People expect a binary response, is it AI generated yes or no. But it's more complicated than that. For example, if you see an emdash, it's probably AI generated. But it can also mean the author used it for fixing grammar or tenses. LLMs can't help but try to help. The same for it's not X, but Y. Sure it's a known pattern, but it's not like people don't use this trope all the time.
In my experience, Pangram is great for detecting an author who is trying to pass someone else's work as theirs, or if they are tackling a subject they have little to no knowledge in.