1 citations · 2 across the 7 of their papers we have counts for
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SwapRec: Warming Up Cold Items Through Training-Time Swaps
Marta Moscati, Jan Malte Lichtenberg, Davide Abbattista +3
Interactions with cold items negatively impact real-time personalization of ID-based recommender systems. This is because the use of such interactions degrades user preference esti…
DenseRec: Revisiting Dense Content Embeddings for Sequential Transformer-based Recommendation
Jan Malte Lichtenberg, Antonio De Candia, Matteo Ruffini
Transformer-based sequential recommenders, such as SASRec or BERT4Rec, typically rely solely on learned item ID embeddings, making them vulnerable to the item cold-start problem, p…
Ranking Across Different Content Types: The Robust Beauty of Multinomial Blending
Jan Malte Lichtenberg, Giuseppe Di Benedetto, Matteo Ruffini
An increasing number of media streaming services have expanded their offerings to include entities of multiple content types. For instance, audio streaming services that started by…
Large Language Models as Recommender Systems: A Study of Popularity Bias
Jan Malte Lichtenberg, Alexander Buchholz, Pola Schwöbel
The issue of popularity bias -- where popular items are disproportionately recommended, overshadowing less popular but potentially relevant items -- remains a significant challenge…