6 citations · 6 across the 12 of their papers we have counts for
3 papers · 1 filter
Exploring Applications of State Space Models and Advanced Training Techniques in Sequential Recommendations: A Comparative Study on Efficiency and Performance
Mark Obozov, Makar Baderko, Stepan Kulibaba +2
Recommender systems aim to estimate the dynamically changing user preferences and sequential dependencies between historical user behaviour and metadata. Although transformer-based…
Optimal Flow Matching: Learning Straight Trajectories in Just One Step
Nikita Kornilov, Petr Mokrov, Alexander Gasnikov +1
Over the several recent years, there has been a boom in development of Flow Matching (FM) methods for generative modeling. One intriguing property pursued by the community is the a…
Activations and Gradients Compression for Model-Parallel Training
Mikhail Rudakov, Aleksandr Beznosikov, Yaroslav Kholodov +1
Large neural networks require enormous computational clusters of machines. Model-parallel training, when the model architecture is partitioned sequentially between workers, is a po…