A human-LLM collaborative pipeline yields EspanStereo, a multi-country Spanish stereotype dataset that exposes region-specific biases in Spanish LLMs and diverges sharply from English-centric resources.
Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques
2 Pith papers cite this work, alongside 4 external citations. Polarity classification is still indexing.
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H-SAL erases latent concepts from text profiles using self-descriptions as implicit debiasing signals and shows competitive performance on a new multi-domain Stack Exchange helpfulness benchmark.
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Scalable and Culturally Specific Stereotype Dataset Construction via Human-LLM Collaboration
A human-LLM collaborative pipeline yields EspanStereo, a multi-country Spanish stereotype dataset that exposes region-specific biases in Spanish LLMs and diverges sharply from English-centric resources.
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Debiasing Without Protected Attributes: Latent Concept Erasure from Textual Profiles
H-SAL erases latent concepts from text profiles using self-descriptions as implicit debiasing signals and shows competitive performance on a new multi-domain Stack Exchange helpfulness benchmark.