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cs.LG2026
Censored LLMs as a Natural Testbed for Secret Knowledge Elicitation
Helena Casademunt, Bartosz CywiÅski, Khoi Tran +3
Large language models sometimes produce false or misleading responses. Two approaches to this problem are honesty elicitation -- modifying prompts or weights so that the model answ…
cs.LG2025
Eliciting Secret Knowledge from Language Models
Bartosz CywiÅski, Emil Ryd, Rowan Wang +4
We study secret elicitation: discovering knowledge that an AI possesses but does not explicitly verbalize. As a testbed, we train three families of large language models (LLMs) to…
cs.LG2025
Inoculation Prompting: Instructing LLMs to misbehave at train-time improves test-time alignment
Nevan Wichers, Aram Ebtekar, Ariana Azarbal +8
Large language models are sometimes trained with imperfect oversight signals, leading to undesired behaviors such as reward hacking and sycophancy. Improving oversight quality can…