46 citations · 61 across the 8 of their papers we have counts for
8 papers
Enhancing Sequential Music Recommendation with Personalized Popularity Awareness
Davide Abbattista, Vito Walter Anelli, Tommaso Di Noia +2
In the realm of music recommendation, sequential recommender systems have shown promise in capturing the dynamic nature of music consumption. Nevertheless, traditional Transformer-…
Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of Items
Aleksandr V. Petrov, Craig Macdonald, Nicola Tonellotto
Transformer-based recommender systems, such as BERT4Rec or SASRec, achieve state-of-the-art results in sequential recommendation. However, it is challenging to use these models in…
Shallow Cross-Encoders for Low-Latency Retrieval
Aleksandr V. Petrov, Sean MacAvaney, Craig Macdonald
Transformer-based Cross-Encoders achieve state-of-the-art effectiveness in text retrieval. However, Cross-Encoders based on large transformer models (such as BERT or T5) are comput…
Aligning GPTRec with Beyond-Accuracy Goals with Reinforcement Learning
Aleksandr Petrov, Craig Macdonald
Adaptations of Transformer models, such as BERT4Rec and SASRec, achieve state-of-the-art performance in the sequential recommendation task according to accuracy-based metrics, such…
gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling
Aleksandr Petrov, Craig Macdonald
A large catalogue size is one of the central challenges in training recommendation models: a large number of items makes them memory and computationally inefficient to compute scor…
MTS Kion Implicit Contextualised Sequential Dataset for Movie Recommendation
Aleksandr Petrov, Ildar Safilo, Daria Tikhonovich +1
We present a new movie and TV show recommendation dataset collected from the real users of MTS Kion video-on-demand platform. In contrast to other popular movie recommendation data…