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Markus Schedl — most-cited papers & profile · Generative Models
← authors
·
overview
Markus Schedl
19
papers ·
126
citations ·
46
h-index
Johannes Kepler University of Linz · Private Pädagogische Hochschule der Diözese Linz · Linz Center of Mechatronics (Austria)
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Most-cited papers
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
2021 · 64 citations
A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios
2024 · 33 citations
Listener Modeling and Context-aware Music Recommendation Based on Country Archetypes
2020 · 21 citations
Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation
2025 · 7 citations
Parameter-Efficient Single Collaborative Branch for Recommendation
2025 · 1 citations
What We Observe as LLM Behavior Can Be a Side-effect of Inference Backend
2026
Music Recommendation with Large Language Models: Challenges, Opportunities, and Evaluation
2025
Investigating Gender Bias in LLM-Generated Stories via Psychological Stereotypes
2025
AI-Generated Song Detection via Lyrics Transcripts
2025
Current Challenges and Visions in Music Recommender Systems Research
2017
A Hybrid Approach to Music Playlist Continuation Based on Playlist-Song Membership
2018
Do Neural Ranking Models Intensify Gender Bias?
2020
Predicting Music Relistening Behavior Using the ACT-R Framework
2021
Unlearning Protected User Attributes in Recommendations with Adversarial Training
2022
Top co-authors
Monorama Swain
· 1
Passant Shafaei
· 1
Shahed Masoudian
· 1
Topics
eess.AS
Collaborative Filtering
cs.SD
Evaluation
Fine-Tuning
Training Techniques
LLM-based
Safety & Alignment
Prompting
Music Generation