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The Multilingual Alignment Prism Aligning Global And Local Preferences To Reduce Harm 2024 06 08

Source
cohere.com
Author
Cohere
Date

Context

Language-model safety tests need to account for whose language and preferences they represent. Cohere's Multilingual Alignment Prism abstract describes human-annotated prompts designed to expose harmful responses, distinguishing broadly shared harms from locally specific ones. The researchers use these prompts to examine approaches across six languages and report strong alignment results with little degradation in general performance. The contribution is a way to evaluate safety across differing cultural and linguistic preferences, rather than treating English-focused harm reduction as sufficient evidence for every audience.

Terms in this piece · Glossary
  • alignment — The work of making AI systems actually pursue what their builders and users intend, rather than something subtly or dangerously different.
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