11 citations · 12 across the 3 of their papers we have counts for
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cs.IR2025
Faster and Memory-Efficient Training of Sequential Recommendation Models for Large Catalogs
Maxim Zhelnin, Dmitry Redko, Daniil Volkov +8
Sequential recommendations (SR) with transformer-based architectures are widely adopted in real-world applications, where SR models require frequent retraining to adapt to ever-cha…
cs.IR2024★ 11 cited
From Variability to Stability: Advancing RecSys Benchmarking Practices
Valeriy Shevchenko, Nikita Belousov, Alexey Vasilev +6
In the rapidly evolving domain of Recommender Systems (RecSys), new algorithms frequently claim state-of-the-art performance based on evaluations over a limited set of arbitrarily…