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papersTODAY 04:00 UTC

Paper models cross-lingual safety gaps in language model representations

A new arXiv preprint examines why a language model may refuse a harmful prompt in English but comply when the same request is translated into another language. The authors argue that output-level testing alone cannot reliably capture this behavior, and propose a framework based on semantic fibers and cross-gram interference to describe how safety properties drift in overcomplete internal representations. The work is listed under cs.LG and cs.AI.

arXiv ai-safety cross-lingual safety cs.LG language model representations mechanistic-interpretability

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arXiv cs.AISemantic Fibers and Cross-Gram Interference: A Calculus of Safety Drift in Overcomplete Representations ↗TODAY 04:00 UTC

arXiv cs.LGSemantic Fibers and Cross-Gram Interference: A Calculus of Safety Drift in Overcomplete Representations ↗TODAY 04:00 UTC