3 papers
cs.IR2026
Contrastive Learning for Diversity-Aware Product Recommendations in Retail
Vasileios Karlis, Ezgi Yıldırım, David Vos +1
Recommender systems often struggle with long-tail distributions and limited item catalog exposure, where a small subset of popular items dominates recommendations. This challenge i…
cs.IR2026
Efficient Optimization of Hierarchical Identifiers for Generative Recommendation
Federica Valeau, Odysseas Boufalis, Polytimi Gkotsi +2
SEATER is a generative retrieval model that improves recommendation inference efficiency and retrieval quality by utilizing balanced tree-structured item identifiers and contrastiv…
cs.IR2025
Revisiting Language Models in Neural News Recommender Systems
Yuyue Zhao, Jin Huang, David Vos +1
Neural news recommender systems (RSs) have integrated language models (LMs) to encode news articles with rich textual information into representations, thereby improving the recomm…