1/20/2026 at 10:18:53 PM
by PaulHoule
1/21/2026 at 12:30:06 AM
Based on Table 1: This method is actually worse than generating a random number (0-100% independent of the program) and testing if it is less than 98.8%. That would achieve a better detection rate without increasing the false positive rate.It doesn't seem worth it to try to follow the math to see if there is something interesting.
by thethirdone
1/21/2026 at 3:55:14 AM
"'Forbidden' AI Technique" (Computerphile)https://www.youtube.com/watch?v=Xx4Tpsk_fnM
"The Hard Problem of Controlling Powerful AI Systems" (Computerphile)
https://www.youtube.com/watch?v=JAcwtV_bFp4
Attempting to guide statistical salience of LLM reasoning model procedures, usually just created an evasive interface facade in the output. =3
by Joel_Mckay
1/20/2026 at 10:55:33 PM
Interesting direction but the 98.8% FPR in Table 1 seems like a dealbreaker. Anyone understand what's going on with the contradictory results between the text and tables?by causalmodels
1/20/2026 at 11:10:24 PM
> Empirically, CTVP attains very good detection rates with reliable false positivesA novel use of the word "reliable"? Jokes aside, either they mean the FPR as the opposite of what you'd expect, the table is not representative of their approach, or they're just... really optimistic?
by dwattttt
1/21/2026 at 6:17:58 AM
> Anyone understand what's going on with the contradictory results between the text and tables?
From Sec 3, end of second to last paragraph
| The protocol is deterministic given fixed RNG seeds, caches model outputsI believe this is a choice, though I think it is suspect that the FPR is pushed this high to get the TP results.
Disclaimer: I only gave this a very cursory skim so don't rely on me too much
by godelski