English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Bias elimination and recent probing studies attempt to remove specificinformation from embedding spaces. Here it is important to remove as much ofthe target information as possible, while preserving any other informationpresent. INLP is a popular recent method which removes specific informationthrough iterative nullspace projections. Multiple iterations, however, increasethe risk that information other than the target is negatively affected. Weintroduce two methods that find a single targeted projection: Mean Projection(MP, more efficient) and Tukey Median Projection (TMP, with theoreticalguarantees). Our comparison between MP and INLP shows that (1) one MPprojection removes linear separability based on the target and (2) MP has lessimpact on the overall space. Further analysis shows that applying randomprojections after MP leads to the same overall effects on the embedding spaceas the multiple projections of INLP. Applying one targeted (MP) projectionhence is methodologically cleaner than applying multiple (INLP) projectionsthat introduce random effects.

Better Hit the Nail on the Head than Beat around the Bush: Removing Protected Attributes with a Single Projection