Pierre Lubitzsch

Pierre Lubitzsch

Ph.D. Student at BIFOLD & TU Berlin

Publications

You can also find my articles on my Google Scholar profile.

Conference Papers

ERASE – A Real-World Aligned Benchmark for Unlearning in Recommender Systems

Published in arXiv preprint, 2026

We present ERASE, a large-scale benchmark for machine unlearning in recommender systems designed to align with real-world usage, spanning collaborative filtering, session-based, and next-basket recommendation.

Recommended citation: Pierre Lubitzsch, Maarten de Rijke, Sebastian Schelter. (2026). "ERASE -- A Real-World Aligned Benchmark for Unlearning in Recommender Systems." Preprint
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Towards a Real-World Aligned Benchmark for Unlearning in Recommender Systems

Published in FAccTRec@RecSys 2025, 2025

We propose design desiderata and research questions to guide the development of a realistic benchmark for machine unlearning in recommender systems, spanning multiple recommendation tasks and unlearning scenarios.

Recommended citation: Pierre Lubitzsch, Olga Ovcharenko, Hao Chen, Maarten de Rijke, Sebastian Schelter. (2025). "Towards a Real-World Aligned Benchmark for Unlearning in Recommender Systems." FAccTRec@RecSys 2025
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