All Stories

  1. Engagement-Driven Content Generation with Large Language Models
  2. Flexible Generation of Preference Data for Recommendation Analysis
  3. Relevance Meets Diversity: A User-Centric Framework for Knowledge Exploration Through Recommendations
  4. Balanced Quality Score: Measuring Popularity Debiasing in Recommendation
  5. Extreme Multi-tagging via Deep Learning and Explanation techniques