3 papers
cs.IR2025
Efficient and Effective Query Context-Aware Learning-to-Rank Model for Sequential Recommendation
Andrii Dzhoha, Alisa Mironenko, Evgeny Labzin +3
Modern sequential recommender systems commonly use transformer-based models for next-item prediction. While these models demonstrate a strong balance between efficiency and quality…
cs.IR2024
Reducing Popularity Influence by Addressing Position Bias
Andrii Dzhoha, Alexey Kurennoy, Vladimir Vlasov +1
Position bias poses a persistent challenge in recommender systems, with much of the existing research focusing on refining ranking relevance and driving user engagement. However, i…
cs.CL2024
Efficient slot labelling
Vladimir Vlasov
Slot labelling is an essential component of any dialogue system, aiming to find important arguments in every user turn. Common approaches involve large pre-trained language models…