Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems
Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval
PhD Student
Gustavo Escobedo, M.Sc.
Johannes Kepler University Linz
Research output
Publications
Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems
Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Audio, Lyrics, Videoclips, Interactions? An Analysis of Uni- and Multi-modal Music Retrieval Systems in Terms of Accuracy and Beyond-accuracy Aspects
Proceedings of the 3rd Music Recommender Systems Workshop (MuRS) co-located with the 19th ACM Conference on Recommender Systems (RecSys 2025), Prague, Czech Republic.
Debiasing Implicit Feedback Recommenders via Sliced Wasserstein Distance-based Regularization
Proceedings of the Nineteenth ACM Conference on Recommender Systems
Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation
Proceedings of the Nineteenth ACM Conference on Recommender Systems
Mitigating Latent User Biases in Pre-trained VAE Recommendation Models via On-demand Input Space Transformation
Proceedings of the Nineteenth ACM Conference on Recommender Systems
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024)
Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training
Proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation (BIAS @ SIGIR 2024)
Computational Versus Perceived Popularity Miscalibration in Recommender Systems
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval