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New calculus models language model safety drift across languages

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new mathematical framework to analyze safety failures in language models, particularly those that occur across different languages. The framework, called "Semantic Fibers and Cross-Gram Interference," uses linear algebra to precisely characterize how a model's safety can degrade when translating harmful requests between languages. It introduces a calibrated exposure measure to distinguish between correctable errors and fundamental issues within the model's representation that cannot be fixed by simply adjusting output parameters. AI

IMPACT Introduces a novel mathematical framework for understanding and potentially mitigating cross-lingual safety failures in language models.

RANK_REASON Academic paper detailing a new theoretical framework for analyzing AI safety. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New calculus models language model safety drift across languages

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Academic paper detailing a new theoretical framework for analyzing AI safety. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Mohammed Ahnouch, Lotfi Elaachack ·

    Semantic Fibers and Cross-Gram Interference: A Calculus of Safety Drift in Overcomplete Representations

    arXiv:2609.14861v1 Announce Type: cross Abstract: A deployed language model may refuse a harmful request in English yet comply with its faithful translation, revealing a cross-lingual safety failure that cannot be characterized reliably by output behavior alone. We formalize this…

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