(TAIMLab) Trustworthy AI in Media Lab

Publications

2025

Khaertdinov, B., Popa, M., and Tintarev, N. (2025). “VisualReF: Interactive Image Search Prototype with Visual Relevance Feedback“. In Proc. of the Nineteenth ACM Conf. on Recommender Systems (RecSys ’25). ACM, New York, NY, USA, 1353–1356. https://doi.org/10.1145/3705328.3759341
 
Zilbershtein, D. (2025). “Fair and Transparent Recommender Systems for Advertisements“. In Proc. of the Nineteenth ACM Conf. on Recommender Systems (RecSys ’25). ACM, New York, NY, USA, 1473–1478. https://doi.org/10.1145/3705328.3748755
 

Kang, J., de Rijke, M., de Leon-Martinez, S., and Oosterhuis, H. “Rethinking Click Models in Light of Carousel Interfaces: Theory-Based Categorization and Design of Click Models“. In Proc. of the 2025 Int. ACM SIGIR Conf. on Innovative Concepts and Theories in Information Retrieval (ICTIR ’25). ACM, New York, NY,
USA, 44–55. https://doi.org/10.1145/3731120.3744585

 

de Leon-Martinez, S., Kang , J., Moro, R.,  de Rijke, M., Kveton, B., Oosterhuis, H. and Bielikova, M. (2025). “RecGaze: The First Eye Tracking and User Interaction Dataset for Carousel Interfaces“. In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’25). Association for Computing Machinery, New York, NY, USA, 3702–3711. https://doi.org/10.1145/3726302.3730301

 
Nachesa, M. K. and Vlad Niculae. 2025. “kNN For Whisper And Its Effect On Bias And Speaker Adaptation”. In Findings of the Association for Computational Linguistics: NAACL 2025, pages 6621–6627, Albuquerque, New Mexico. Association for Computational Linguistics.
 

2024

A. Ganesh, M. Popa, D. Odijk, and N. Tintarev. “Does spatio-temporal information benefit the video summarization task?” In AEQUITAS 2024: Workshop on Fairness and Bias in AI| co-located with ECAI 2024, pages 10–25, 2024
 
Zilbershtein D., Barile F., Odijk D., Tintarev N., “Bridging the Transparency Gap: Exploring Multi-Stakeholder Preferences for Targeted Advertisement Explanations“, (2024) CEUR Workshop Proceedings, 3815, pp. 46 – 58.
 
Kang, J., de Rijke, M. and Oosterhuis, H. “Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted Trees”, ACM SIGIR 2024.
 
Tintarev, N., Knijnenburg, B. and Willemsen, M. “Measuring the Benefit of Increased Transparency and Control in News Recommendation“, AI Magazine, 2024.

2023

Granada, M. G., Zilbershtein, D., Odijk, D. & Barile, F. (2023) “VideolandGPT: A User Study on a Conversational Recommender System“, 1 Jan 2023, In: CEUR Workshop Proceedings.3560, p. 44-496.