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cs.IR2026
Controllable and Content-Based Recommendations
Fırat Öncel, Jihoon Jeong, Emiliano Penaloza +3
Traditional recommendation systems rely on latent (dense) representations, making them difficult to interpret and control. We propose the Controllable and Content-Based Recommendat…
cs.IR2025
Audio Prototypical Network For Controllable Music Recommendation
Fırat Öncel, Emiliano Penaloza, Haolun Wu +4
Traditional recommendation systems represent user preferences in dense representations obtained through black-box encoder models. While these models often provide strong recommenda…