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Center for Language and Cognition, University of Groningen
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Human-like color categories can emerge in neural agents by simply upsampling rare color terms and training with multiple listeners, closing the gap between artificial and human color lexicons.
Multilingual LLMs can be made significantly more reliable by directly optimizing for crosslingual consistency using a DPO-inspired method that requires no explicit reward model.
