3 papers
cs.IR2025
eSASRec: Enhancing Transformer-based Recommendations in a Modular Fashion
Daria Tikhonovich, Nikita Zelinskiy, Aleksandr V. Petrov +4
Since their introduction, Transformer-based models, such as SASRec and BERT4Rec, have become common baselines for sequential recommendations, surpassing earlier neural and non-neur…
cs.LG2025
Simplicial SMOTE: Oversampling Solution to the Imbalanced Learning Problem
Oleg Kachan, Andrey Savchenko, Gleb Gusev
SMOTE (Synthetic Minority Oversampling Technique) is the established geometric approach to random oversampling to balance classes in the imbalanced learning problem, followed by ma…
cs.IR2024
LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering
Nikita Severin, Aleksei Ziablitsev, Yulia Savelyeva +8
We present LLM-KT, a flexible framework designed to enhance collaborative filtering (CF) models by seamlessly integrating LLM (Large Language Model)-generated features. Unlike exis…