Computational Versus Perceived Popularity Miscalibration in Recommender Systems. - Oleg Lesota; Gustavo Escobedo; Yashar Deldjoo; Bruce Ferwerda; Simone Kopeinik; Elisabeth Lex; Navid Rekabsaz; Markus Schedl (SIGIR, 2023)

Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training. - Gustavo Escobedo; Christian Ganhör; Stefan Brandl; Mirjam Augstein; Markus Schedl (BIAS, 2024)

Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models. - Gustavo Escobedo; Marta Moscati; Peter Muellner; Simone Kopeinik; Dominik Kowald; Elisabeth Lex; Markus Schedl (ECML/PKDD (7), 2024)

Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation. - Alessandro B. Melchiorre; Elena V. Epure; Shahed Masoudian; Gustavo Escobedo; Anna Hausberger; Manuel Moussallam; Markus Schedl (CoRR, 2025)

Investigating Gender Bias in LLM-Generated Stories via Psychological Stereotypes. - Shahed Masoudian; Gustavo Escobedo; Hannah Strauß; Markus Schedl (CoRR, 2025)