Fırat Öncel

Doctorat - Concordia

Superviseur⋅e principal⋅e

Mirco Ravanelli

Co-supervisor

Laurent Charlin

Sujets de recherche

Apprentissage de représentations

Apprentissage profond

Systèmes de recommandation

Site web

Google Scholar

GitHub

Publications

Audio Prototypical Network for Controllable Music Recommendation

Traditional recommendation systems represent user preferences in dense representations obtained through black-box encoder models. While thes… (voir plus)e models often provide strong recommendation performance, they lack interpretability for users, leaving users unable to understand or control the system’s modeling of their preferences. This limitation is especially challenging in music recommendation, where user preferences are highly personal and often evolve based on nuanced qualities like mood, genre, tempo, or instrumentation. In this paper, we propose an audio prototypical network for controllable music recommendation. This network expresses user preferences in terms of prototypes representative of semantically meaningful features pertaining to musical qualities. We show that the model obtains competitive recommendation performance compared to popular baseline models while also providing interpretable and controllable user profiles.

2025-08-01

arXiv (publié)

doi.org

openreview.net

Adaptation Odyssey in LLMs: Why Does Additional Pretraining Sometimes Fail to Improve?

Fırat Öncel

Matthias Bethge

Beyza Ermis

Mirco Ravanelli

Cem Subakan

cCaugatay Yildiz

2024-01-01