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Niklas Herbster

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#machine learning Preprint Oct 2026

CAT-alyzing Honesty: Continuous Adversarial Training for Transferable LLM Honesty

Large language models (LLMs) are becoming prevalent in scenarios where honesty is critical. However, despite alignment training, these models still exhibit dishonest behaviour, such as outputting claims that contradict some knowledge or are not supported by what is accessible in context. We introduce Continuous Adversa...

Yuan-Chen Chang, Niklas Herbster, G. Gidel et al. · 1 citation

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