Oleg Lesota

33 papers A* 4A 5B 3Misc 1Journal 14Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems.
CoRR
Zihan Li, Gustavo Escobedo, Marta Moscati, Oleg Lesota, Markus Schedl
2026 — conf
Extending Logic Tensor Networks to Implicit Feedback for Representation-Aware Music Recommendation.
ECIR (3)
Hannah Eckert, Oleg Lesota, Markus Schedl
2025 — conf
Enhancing Music Recommender Systems with Multimedia Content: A Context-Aware Approach.
ISMIR
Oleg Lesota, Veronica Clavijo, Attia Rizwani, Markus Schedl, Bruce Ferwerda
2025 A conf
Fine-tuning for Inference-efficient Calibrated Recommendations.
RecSys
Oleg Lesota, Adrian Bajko, Max Walder, Matthias Wenzel, Antonela Tommasel, Markus Schedl
2025 J jnl
Iguanodon: A Code-Breaking Game for Improving Visualization Construction Literacy.
IEEE Trans. Vis. Comput. Graph.
Patrick Adelberger, Oleg Lesota, Klaus Eckelt, Markus Schedl, Marc Streit
2025 A conf
Investigating Carbon Footprint of Recommender Systems Beyond Training Time.
RecSys
Josef Schodl, Oleg Lesota, Antonela Tommasel, Markus Schedl
2025 — conf
Investigating Music Track Liking in the Halo of Album Covers.
ISMIR
Oleg Lesota, Anna Hausberger, Ivanna Pshenychna, Oleksandr Shvydanenko, Olha Yehorova, Markus Schedl
2024 A conf
Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems.
RecSys
Oleg Lesota, Jonas Geiger, Max Walder, Dominik Kowald, Markus Schedl
2024 J jnl
Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems.
CoRR
Oleg Lesota, Jonas Geiger, Max Walder, Dominik Kowald, Markus Schedl
2024 J jnl
Spin-Wave Voices: Sonification of Nanoscale Spin Waves as an Engagement and Research Tool.
CoRR
Santa Pile, Oleg Lesota, Silvan David Peter, Christina Humer, Martin Gasser
2024 J jnl
The Importance of Cognitive Biases in the Recommendation Ecosystem.
CoRR
Markus Schedl, Oleg Lesota, Stefan Brandl, Mohammad Lotfi, Gustavo Junior Escobedo Ticona, Shahed Masoudian
2024 — conf
The Importance of Cognitive Biases in the Recommendation Ecosystem: Evidence of Feature-Positive Effect, Ikea Effect, and Cultural Homophily.
IntRS@RecSys
Markus Schedl, Oleg Lesota, Shahed Masoudian
2023 A* conf
Computational Versus Perceived Popularity Miscalibration in Recommender Systems.
SIGIR
Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz, Markus Schedl
2023 J jnl
Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation.
Int. J. Multim. Inf. Retr.
Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Fritzl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl
2023 B conf
Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results.
CHIIR
Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz
2023 A conf
Parameter-efficient Modularised Bias Mitigation via AdapterFusion.
EACL
Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz
2023 J jnl
Parameter-efficient Modularised Bias Mitigation via AdapterFusion.
CoRR
Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz
2022 B conf
EmoMTB: Emotion-aware Music Tower Blocks.
ICMR
Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Friztl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl
2022 — conf
Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization.
MORS@RecSys
Oleg Lesota, Stefan Brandl, Matthias Wenzel, Alessandro B. Melchiorre, Elisabeth Lex, Navid Rekabsaz, Markus Schedl
2022 J jnl
Grep-BiasIR: A Dataset for Investigating Gender Representation-Bias in Information Retrieval Results.
CoRR
Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz
2022 B conf
LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis.
CHIIR
Markus Schedl, Stefan Brandl, Oleg Lesota, Emilia Parada-Cabaleiro, David Penz, Navid Rekabsaz
2022 — conf
Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms.
ISMIR
Oleg Lesota, Emilia Parada-Cabaleiro, Stefan Brandl, Elisabeth Lex, Navid Rekabsaz, Markus Schedl
2022 A* conf
Unlearning Protected User Attributes in Recommendations with Adversarial Training.
SIGIR
Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl
2022 J jnl
Unlearning Protected User Attributes in Recommendations with Adversarial Training.
CoRR
Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl
2021 Misc conf
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models.
ICTIR
Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl
2021 J jnl
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models.
CoRR
Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl
2021 A conf
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
RecSys
Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl
2021 J jnl
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
CoRR
Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl
2021 J jnl
Investigating gender fairness of recommendation algorithms in the music domain.
Inf. Process. Manag.
Alessandro B. Melchiorre, Navid Rekabsaz, Emilia Parada-Cabaleiro, Stefan Brandl, Oleg Lesota, Markus Schedl
2021 A* conf
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models.
SIGIR
Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff
2021 J jnl
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models.
CoRR
Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff
2021 A* conf
TripClick: The Log Files of a Large Health Web Search Engine.
SIGIR
Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff
2021 J jnl
TripClick: The Log Files of a Large Health Web Search Engine.
CoRR
Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff