Bold of you to assume that you will have any idea at all that an LLM generated a particular comment.
If I take a trick like those recommend by the authors of min_p (high temperature + min_p)[1], I do a great job of escaping the "slop" phrasing that is normally detectable and indicative of an LLM. Even more-so if I use the anti-slop sampler[2].
LLMs are already more creative than humans are today, they're already better than humans at most kinds of writing, and they are coming to a comment section near you.
Good luck proving I didn't use an LLM to generate this comment. What if I did? I claim that I might as well have. Maybe I did? :)
Fascinating that very minor variations on established sampling techniques still generate papers. :) Afaik, neither top-p nor top-k sampling has conclusively been proven superior to good old-fashioned temperature sampling. Certainly, recent sampling techniques can make the text "sound different", but not necessarily read better. I.e., you're replacing one kind of bot generated "slop" with another.
Just FYI. This paper is currently ranked in the top 10 papers in all of ICLR, out of 12000 submissions. It's telling that peer reviewers believe that it deserves to be highlighted.
Maybe I'm wrong then. But there has been many slightly-different-sampling-method papers in the past that showed impressive results which were then difficult to replicate on other models or experimental setups.
Comments
Bold of you to assume that you will have any idea at all that an LLM generated a particular comment.
If I take a trick like those recommend by the authors of min_p (high temperature + min_p)[1], I do a great job of escaping the "slop" phrasing that is normally detectable and indicative of an LLM. Even more-so if I use the anti-slop sampler[2].
LLMs are already more creative than humans are today, they're already better than humans at most kinds of writing, and they are coming to a comment section near you.
Good luck proving I didn't use an LLM to generate this comment. What if I did? I claim that I might as well have. Maybe I did? :)
[1] https://openreview.net/forum?id=FBkpCyujtS
[2] https://github.com/sam-paech/antislop-sampler, https://github.com/sam-paech/antislop-sampler/blob/main/slop...
Fascinating that very minor variations on established sampling techniques still generate papers. :) Afaik, neither top-p nor top-k sampling has conclusively been proven superior to good old-fashioned temperature sampling. Certainly, recent sampling techniques can make the text "sound different", but not necessarily read better. I.e., you're replacing one kind of bot generated "slop" with another.
Just FYI. This paper is currently ranked in the top 10 papers in all of ICLR, out of 12000 submissions. It's telling that peer reviewers believe that it deserves to be highlighted.
Maybe I'm wrong then. But there has been many slightly-different-sampling-method papers in the past that showed impressive results which were then difficult to replicate on other models or experimental setups.