Sycophancy as a Multilingual Alignment Failure: How Safety Degrades Across Languages, Topics, and Models

Safety-aligned large language models often exhibit sycophancy, which is the tendency to affirm users' opinions regardless of factual accuracy. Although well-studied in English, its manifestation in other languages remains largely unexamined, leaving billions of non-English speakers potentially vulnerable to model-validated misinformation. We present the first large-scale, multi-model evaluation of cross-lingual sycophancy, benchmarking \textbf{six instruction-tuned models} across \textbf{1.1 mil

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ethics.ai (7 June 2026), “Sycophancy as a Multilingual Alignment Failure: How Safety Degrades Across Languages, Topics, and Models,” evidence record 1307, https://ethics.ai/record/1307 (originally published by arXiv).

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