2 papers
cs.CL2025
Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation
Tomasz Limisiewicz, David MareÄek, Tomáš Musil
Mitigation of biases, such as language models' reliance on gender stereotypes, is a crucial endeavor required for the creation of reliable and useful language technology. The cruci…
cs.CL2024
Transforming Hidden States into Binary Semantic Features
Tomáš Musil, David MareÄek
Large language models follow a lineage of many NLP applications that were directly inspired by distributional semantics, but do not seem to be closely related to it anymore. In thi…