Multiperspective and Multidisciplinary Treatment of Fairness in Recommender Systems Research. - Markus Schedl; Navid Rekabsaz; Elisabeth Lex; Tessa Grosz; Elisabeth Greif (UMAP (Adjunct Publication), 2022)

Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning. - Deepak Kumar; Tessa Grosz; Elisabeth Greif; Navid Rekabsaz; Markus Schedl (HR@RecSys, 2023)

Fairness of recommender systems in the recruitment domain: an analysis from technical and legal perspectives. - Deepak Kumar; Tessa Grosz; Navid Rekabsaz; Elisabeth Greif; Markus Schedl (Frontiers Big Data, 2024)