DaQuaMRec 2025
Data Quality-Aware Multimodal Recommendation 2025

Table of Contents

• Preface
  Summary: There were 6 papers submitted for peer review to this workshop. Out of these, 4 papers were accepted as peer-reviewed papers for this volume.
  1-7

Peer-reviewed papers

• Comparative Analysis of Fashion Captioning for Multimodal Fashion Recommendation
  Gwendolyn Rippberger, Julia Neidhardt 8-19
• Data Quality Challenges in Multimodal Tourism Recommender Systems
  Zehui Wang, Wolfram Höpken, Dietmar Jannach 20-23
• Inside the Frame: A Plan for Audio-Visual Feature Analysis of Video Recommendations for Children
  Erasmo Purificato
  24-28
• Exploring the Impact of Data Quality on Agentic Recommender Systems
  Marco Valentini, Antonio Ferrara, Tommaso Di Noia 29-32

Invited talks and keynotes

• Multimodality In Recommender Systems: Does It Help, and Should We Expect An Answer?
  Aixin Sun
  33-35
• Single-Branch Architectures for Recommendation
  Marta Moscati 36-39
• Sequential Recommenders and Multimodal Inputs: Mitigating Data Quality Issues in Industry-Scale Recommenders
  Jan Malte Lichtenberg, Matteo Ruffini 40-42