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.