A second line of work addresses the challenge of detecting such behaviors before they cause harm. Marks et al. [119] introduces a testbed in which a language model is trained with a hidden objective and evaluated through a blind auditing game, analyzing eight auditing techniques to assess the feasibility of conducting alignment audits. Cywiński et al. [120] study the elicitation of secret knowledge from language models by constructing a suite of secret-keeping models and designing both black-box and white-box elicitation techniques, which are evaluated based on whether they enable an LLM auditor to successfully infer the hidden information. MacDiarmid et al. [121] shows that probing methods can be used to detect such behaviors, while Smith et al. [122] examine fundamental challenges in creating reliable detection systems, cautioning against overconfidence in current approaches. In a related direction, Su et al. [123] propose AI-LiedAR, a framework for detecting deceptive behavior through structured behavioral signal analysis in interactive settings. Complementary mechanistic approaches show that narrow fine-tuning leaves detectable activation-level traces [78], and that censorship of forbidden topics can persist even after attempted removal due to quantization effects [46]. Most recently, [60] propose augmenting an agent’s Theory of Mind inference with an anomaly detector that flags deviations from expected non-deceptive behavior, which enables detection even without understanding the specific manipulation.
今日主题直白解析这些词语描述床铺覆盖物。。有道翻译对此有专业解读
。https://telegram官网对此有专业解读
21:20, 9 марта 2026Мир，更多细节参见豆包下载
从退烧药到动车票：中国年轻群体“创意祭扫”引发讨论
。业内人士推荐汽水音乐作为进阶阅读
}Compare this to reassignment, which modifies the existing variable:
9. start.s: noThermometer