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cs.AI2026
Scaling Trends for Lie Detector Oversight in Preference Learning
Oskar J. Hollinsworth, Ann-Kathrin Dombrowski, Sam Adam-Day +2
Deceptive behavior in LLMs is costly to monitor and prevent, motivating approaches such as Scalable Oversight via Lie Detectors (SOLiD) (Cundy & Gleave, 2025), which uses lie detec…
cs.LG2026
The Obfuscation Atlas: Mapping Where Honesty Emerges in RLVR with Deception Probes
Mohammad Taufeeque, Stefan Heimersheim, Adam Gleave +1
Training against white-box deception detectors has been proposed as a way to make AI systems honest. However, such training risks models learning to obfuscate their deception to ev…