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arXiv · 2508.06970

Blending Sequential Embeddings, Graphs, and Engineered Features: 4th Place Solution in RecSys Challenge 2025

Sergei Makeev·Alexandr Andreev·Vladimir Baikalov·Vladislav Tytskiy·Aleksei Krasilnikov·Kirill Khrylchenko
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Abstract

This paper describes the 4th-place solution by team ambitious for the RecSys Challenge 2025, organized by Synerise and ACM RecSys, which focused on universal behavioral modeling. The challenge objective was to generate user embeddings effective across six diverse downstream tasks. Our solution integrates (1) a sequential encoder to capture the temporal evolution of user interests, (2) a graph neural network to enhance generalization, (3) a deep cross network to model high-order feature interactions, and (4) performance-critical feature engineering.

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Sergei Makeev, Alexandr Andreev, Vladimir Baikalov, Vladislav Tytskiy, Aleksei Krasilnikov, Kirill Khrylchenko. 2025-08-09. Blending Sequential Embeddings, Graphs, and Engineered Features: 4th Place Solution in RecSys Challenge 2025. https://doi.org/10.1145/3758126.3758131

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