Gustavo Escobedo

According to our database, Gustavo Escobedo authored at least 8 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems.

Zihan Li, Gustavo Escobedo, Marta Moscati, Oleg Lesota, Markus Schedl

CoRR, February, 2026

2025

Investigating Gender Bias in LLM-Generated Stories via Psychological Stereotypes.

Shahed Masoudian, Gustavo Escobedo, Hannah Strauß, Markus Schedl

CoRR, August, 2025

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

Proceedings of the Nineteenth ACM Conference on Recommender Systems, 2025

Debiasing Implicit Feedback Recommenders via Sliced Wasserstein Distance-based Regularization.

Gustavo Escobedo, David Penz, Markus Schedl

Proceedings of the Nineteenth ACM Conference on Recommender Systems, 2025

Audio, Lyrics, Videoclips, Interactions? An Analysis of Uni- and Multi-modal Music Retrieval Systems in Terms of Accuracy and Beyond-accuracy Aspects.

Marta Moscati, Gustavo Escobedo, Eduardo Hernandez Almanza, Jonas Peché, Markus Schedl

Proceedings of the 3rd Music Recommender Systems Workshop (MuRS 2025) co-located with the 19th ACM Conference on Recommender Systems (RecSys 2025), 2025

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

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training.

Gustavo Escobedo, Christian Ganhör, Stefan Brandl, Mirjam Augstein, Markus Schedl

Proceedings of the Advances in Bias and Fairness in Information Retrieval, 2024

2023

Computational Versus Perceived Popularity Miscalibration in Recommender Systems.

Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz, Markus Schedl

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023