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Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models
Research article (Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021) · cited 55× · AI/ML
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APA4ort.xyz Knowledge Graph. (2026). Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models. Retrieved May 24, 2026, from https://4ort.xyz/entity/stereotype-and-skew-quantifying-gender-bias-in-pre-trained-and-fine-tuned-language-models
MLA“Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/stereotype-and-skew-quantifying-gender-bias-in-pre-trained-and-fine-tuned-language-models.
BibTeX@misc{4ortxyz_stereotype-and-skew-quantifying-gender-bias-in-pre-trained-and-fine-tuned-language-models_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models}}, year = {2026}, url = {https://4ort.xyz/entity/stereotype-and-skew-quantifying-gender-bias-in-pre-trained-and-fine-tuned-language-models}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models — https://4ort.xyz/entity/stereotype-and-skew-quantifying-gender-bias-in-pre-trained-and-fine-tuned-language-models (retrieved 2026-05-24)
