| 2026 | ECIR | Extending Logic Tensor Networks to Implicit Feedback for Representation-Aware Music Recommendation. | Hannah Eckert, Oleg Lesota, Markus Schedl |
| 2026 | SIGIR | Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems. | Zihan Li, Gustavo Escobedo, Marta Moscati, Oleg Lesota, Markus Schedl |
| 2025 | RecSys | Fine-tuning for Inference-efficient Calibrated Recommendations. | Oleg Lesota, Adrian Bajko, Max Walder, Matthias Wenzel, Antonela Tommasel, Markus Schedl |
| 2025 | RecSys | Investigating Carbon Footprint of Recommender Systems Beyond Training Time. | Josef Schodl, Oleg Lesota, Antonela Tommasel, Markus Schedl |
| 2024 | RecSys | Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems. | Oleg Lesota, Jonas Geiger, Max Walder, Dominik Kowald, Markus Schedl |
| 2023 | CHIIR | Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results. | Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz |
| 2023 | EACL | Parameter-efficient Modularised Bias Mitigation via AdapterFusion. | Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz |
| 2023 | SIGIR | Computational Versus Perceived Popularity Miscalibration in Recommender Systems. | Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz, Markus Schedl |
| 2022 | CHIIR | LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis. | Markus Schedl, Stefan Brandl, Oleg Lesota, Emilia Parada-Cabaleiro, David Penz, Navid Rekabsaz |
| 2022 | RecSys | Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization. | Oleg Lesota, Stefan Brandl, Matthias Wenzel, Alessandro B. Melchiorre, Elisabeth Lex, Navid Rekabsaz, Markus Schedl |
| 2022 | SIGIR | Unlearning Protected User Attributes in Recommendations with Adversarial Training. | Christian Ganhr, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl |
| 2021 | ICTIR | A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models. | Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl |
| 2021 | RecSys | Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? | Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl |
| 2021 | SIGIR | Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models. | Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff |
| 2021 | SIGIR | TripClick: The Log Files of a Large Health Web Search Engine. | Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff |