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

arXiv: https://arxiv.org/abs/2508.06970 · HTML: https://mlsanity.com/paper/2508.06970/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Aug 2025.

## Built on by (most cited first, 1 of 1)

- [A Foundation Model for Multimodal Event Sequences in Financial Applications](https://mlsanity.com/paper/2607.09955/) (2026)

## Abstract (arXiv)

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.