Publications

2025

1. 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, and Markus Schedl

   In Proceedings of the Nineteenth ACM Conference on Recommender Systems, 2025

   Bib

   @inproceedings{melchiorre2025just,
     title = {Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation},
     author = {Melchiorre, Alessandro B and Epure, Elena V and Masoudian, Shahed and Escobedo, Gustavo and Hausberger, Anna and Moussallam, Manuel and Schedl, Markus},
     booktitle = {Proceedings of the Nineteenth ACM Conference on Recommender Systems},
     pages = {615--620},
     year = {2025},
   }

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

   Shahed Masoudian, Gustavo Escobedo, Hannah Strauss, and Markus Schedl

   arXiv preprint arXiv:2508.03292, 2025

   Bib

   @article{masoudian2025investigating,
     title = {Investigating Gender Bias in LLM-Generated Stories via Psychological Stereotypes},
     author = {Masoudian, Shahed and Escobedo, Gustavo and Strauss, Hannah and Schedl, Markus},
     journal = {arXiv preprint arXiv:2508.03292},
     year = {2025},
   }

3. 

   Debiasing Implicit Feedback Recommenders via Sliced Wasserstein Distance-based Regularization

   Gustavo Escobedo, David Penz, and Markus Schedl

   In Proceedings of the Nineteenth ACM Conference on Recommender Systems, 2025

   Bib

   @inproceedings{escobedo2025debiasing,
     title = {Debiasing Implicit Feedback Recommenders via Sliced Wasserstein Distance-based Regularization},
     author = {Escobedo, Gustavo and Penz, David and Schedl, Markus},
     booktitle = {Proceedings of the Nineteenth ACM Conference on Recommender Systems},
     pages = {1153--1158},
     year = {2025},
   }

4. 

   Mitigating Latent User Biases in Pre-trained VAE Recommendation Models via On-demand Input Space Transformation

   David Penz, Gustavo Escobedo, and Markus Schedl

   In Proceedings of the Nineteenth ACM Conference on Recommender Systems, 2025

   Bib

   @inproceedings{penz2025mitigating,
     title = {Mitigating Latent User Biases in Pre-trained VAE Recommendation Models via On-demand Input Space Transformation},
     author = {Penz, David and Escobedo, Gustavo and Schedl, Markus},
     booktitle = {Proceedings of the Nineteenth ACM Conference on Recommender Systems},
     pages = {632--636},
     year = {2025},
   }

2024

1. 

   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, and Markus Schedl

   In Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VII, 2024

   Bib HTML PDF

   @inproceedings{DBLP:conf/pkdd/EscobedoMMKKLS24,
     author = {Escobedo, Gustavo and Moscati, Marta and Muellner, Peter and Kopeinik, Simone and Kowald, Dominik and Lex, Elisabeth and Schedl, Markus},
     editor = {Bifet, Albert and Davis, Jesse and Krilavicius, Tomas and Kull, Meelis and Ntoutsi, Eirini and Zliobaite, Indre},
     title = {Making Alice Appear Like Bob: {A} Probabilistic Preference Obfuscation
                       Method For Implicit Feedback Recommendation Models},
     booktitle = {Machine Learning and Knowledge Discovery in Databases. Research Track
                       - European Conference, {ECML} {PKDD} 2024, Vilnius, Lithuania, September
                       9-13, 2024, Proceedings, Part {VII}},
     series = {Lecture Notes in Computer Science},
     volume = {14947},
     pages = {349--365},
     publisher = {Springer},
     year = {2024},
     url = {https://doi.org/10.1007/978-3-031-70368-3\_21},
     doi = {10.1007/978-3-031-70368-3\_21},
   }

2. 

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

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

   In Proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation BIAS @ SIGIR (2024), 2024

   Bib PDF

   @inproceedings{DBLP:conf/sigir/EscobedoRSDLL24,
     author = {Escobedo, Gustavo and Ganh{\"{o}}r, Christian and Brandl, Stefan and Augstein, Mirjam and Schedl, Markus},
     title = {Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training},
     booktitle = {Proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation BIAS @ SIGIR (2024)},
     year = {2024},
   }

2023

1. Computational Versus Perceived Popularity Miscalibration in Recommender Systems

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

   In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23-27, 2023, 2023

   Bib HTML

   @inproceedings{DBLP:conf/sigir/LesotaEDFKLRS23,
     author = {Lesota, Oleg and Escobedo, Gustavo and Deldjoo, Yashar and Ferwerda, Bruce and Kopeinik, Simone and Lex, Elisabeth and Rekabsaz, Navid and Schedl, Markus},
     editor = {Chen, Hsin{-}Hsi and Duh, Wei{-}Jou (Edward) and Huang, Hen{-}Hsen and Kato, Makoto P. and Mothe, Josiane and Poblete, Barbara},
     title = {Computational Versus Perceived Popularity Miscalibration in Recommender
                       Systems},
     booktitle = {Proceedings of the 46th International {ACM} {SIGIR} Conference on
                       Research and Development in Information Retrieval, {SIGIR} 2023, Taipei,
                       Taiwan, July 23-27, 2023},
     pages = {1889--1893},
     publisher = {{ACM}},
     year = {2023},
     url = {https://doi.org/10.1145/3539618.3591964},
     doi = {10.1145/3539618.3591964},
   }