Schützen is a German-Bulgarian LLM safety dataset showing pronounced cross-language differences in model safety behavior.
What Can We Learn from Collective Human Opinions on Natural Language Inference Data? , url =
2 Pith papers cite this work, alongside 77 external citations. Polarity classification is still indexing.
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A statistical framework decomposes human annotation outcomes into four interpretable variation sources and extends classical measurement-error models to handle both shared and individualized notions of truth.
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Sch\"utzen: Evaluating LLM Safety in Bulgarian and German Contexts
Schützen is a German-Bulgarian LLM safety dataset showing pronounced cross-language differences in model safety behavior.
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From Ground Truth to Measurement: A Statistical Framework for Human Labeling
A statistical framework decomposes human annotation outcomes into four interpretable variation sources and extends classical measurement-error models to handle both shared and individualized notions of truth.