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Johan Pauwels

4 papers hereh-index 210 citations4 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.SD2
  • cs.IR1
  • cs.LG1
same name
  • Johan Pauwels — 6 papers, h 3
  • Johan Pauwels — 3 papers, h 12
  • Johan Pauwels — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedEvaluation of pretrained language models on music understanding

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.IR2026

Leveraging Artist Catalogs for Cold-Start Music Recommendation

Yan-Martin Tamm, Gregor Meehan, Vojtěch Nekl +4

The item cold-start problem poses a fundamental challenge for music recommendation: newly added tracks lack the interaction history that collaborative filtering (CF) requires. Exis…

cs.SD2026

Towards Effective Negation Modeling in Joint Audio-Text Models for Music

Yannis Vasilakis, Rachel Bittner, Johan Pauwels

Joint audio-text models are widely used for music retrieval, yet they struggle with semantic phenomena such as negation. Negation is fundamental for distinguishing the absence (or…

cs.LG2024★ 1 cited

Evaluation of pretrained language models on music understanding

Yannis Vasilakis, Rachel Bittner, Johan Pauwels

Music-text multimodal systems have enabled new approaches to Music Information Research (MIR) applications such as audio-to-text and text-to-audio retrieval, text-based song genera…

cs.SD2024

I can listen but cannot read: An evaluation of two-tower multimodal systems for instrument recognition

Yannis Vasilakis, Rachel Bittner, Johan Pauwels

Music two-tower multimodal systems integrate audio and text modalities into a joint audio-text space, enabling direct comparison between songs and their corresponding labels. These…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.