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Detecting Strategic Deception Using Linear Probes, (2023)) and one of re-sponses to simple roleplaying scenarios. Feb 5, 2025 · We thus evaluate if linear probes can robustly detect deception by monitoring model activations. 6-27B-eval_sandbagger using residual stream activations, following the methodology from Detecting Strategic Deception in Language Models (Apollo Research, 2024). 19755–19786 8 36 See, Schneider, Johannes, Christian Meske, and Michalis Vlachos. , 2023) and one of responses to simple roleplaying scenarios. The BLAST (TM) Deception Detection Certified Training Program is owned by Whetst Bibliographic details on Detecting Strategic Deception Using Linear Probes. Monitoring outputs alone is insufficient, since the AI might produce seemingly benign outputs while their internal reasoning is misaligned. , Heimersheim, S. Learn to accurately detect when someone is lying to you with amazing accuracy. We test two probe-training datasets, one with con-trasting instructions to be honest or deceptive (following Zou et al. " Proceedings of the 42nd International Conference on Machine Learning, Proceedings of Machine Learning Research, vol. "Detecting Strategic Deception with Linear Probes. 6-27B:ai-safety-institute/Qwen3. Excerpts of my interview with Mark McClich, former Secret Service Agent and creator of Statement Analysis, a technique applied by the FBI to detect deception in the words we speak. May 1, 2025 · How can we spot that kind of strategic deception before it causes harm? We explore a simple detector system: a linear probe that monitors the model's internal thoughts (its 'activations', or intermediate computations)—while the model responds. Detecting Strategic Deception Using Linear Probes Nicholas Goldowsky-Dill , Bilal Chughtai , Stefan Heimersheim , Can you tell when an LLM is lying from the activations? Are simple methods good enough? We recently published a paper investigating if linear probes detect when Llama is deceptive. We thus Feb 5, 2025 · Researchers at Apollo Research demonstrate that linear probes can effectively detect strategic deception in large language models by analyzing internal act 5 days ago · A probe trained to detect deceptive behaviour in Qwen/Qwen3. May 1, 2025 · We thus evaluate if linear probes can robustly detect deception by monitoring model activations. . Mar 19, 2026 · IEEE Access, vol. May 2, 2023 – Lies and Allies TuesdaysDavid Neequaye – What justifies cognitive load lie detection? We thus evaluate if linear probes can robustly detect de-ception by monitoring model activations. , Chughtai, B. Detecting strategic deception with linear probes. AI models might use deceptive strategies as part of scheming or misaligned behaviour. , and Hobbhahn, M. We thus evaluate if linear probes can robustly detect deception by monitoring model activations. In Forty-second International Conference on Machine Learning, 2025. 18757–18775; Goldowsky-Dill, Nicholas, et al. We test two probe-training datasets, one with contrasting instructions to It is found that white-box probes are promising for future monitoring systems, but current performance is insufficient as a robust defence against deception. Feb 6, 2025 · We thus evaluate if linear probes can robustly detect deception by monitoring model activations. How can we spot that kind of strategic deception before it causes harm?We explore a simple detector system: a linear probe that monitors the model's internal thoughts (its 'activations', or intermediate computations)—while the model responds. We test two probe-training datasets, one with contrasting instructions to be honest or deceptive (following Zou et al. 10, 2022, pp. 267, 2025, pp. (2023)) and one of responses to simple roleplaying scenarios. Feb 6, 2025 · We test two probe-training datasets, one with contrasting instructions to be honest or deceptive (following Zou et al. Feb 17, 2026 · Goldowsky-Dill, N. hw5 gtge ta sib4qd uhfj rt jh ahua bvci arzig1