mlsanityData to 14 Oct 2026

Beyond Isolated Clients: Integrating Graph-Based Embeddings into Event Sequence Models

arXiv 2604.09085 ↗First posted 10 Apr 2026cs.LG cs.AIcited by 0

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Abstract (arXiv)

Large-scale digital platforms generate billions of timestamped user-item interactions (events) that are crucial for predicting user attributes in, e.g., fraud prevention and recommendations. While self-supervised learning (SSL) effectively models the temporal order of events, it typically overlooks the global structure of the user-item interaction graph. To bridge this gap, we propose three model-agnostic strategies for integrating this structural information into contrastive SSL: enriching event embeddings, aligning client representations with graph embeddings, and adding a structural pretext task. Experiments on four financial and e-commerce datasets demonstrate that our approach consistently improves the accuracy (up to a 2.3% AUC) and reveals that graph density is a key factor in selecting the optimal integration strategy.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 17 references that are in the map. First posted on arXiv 10 Apr 2026.

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References · 12

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
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  3. 2017Graph Attention Networkscited by 8,923
  4. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
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  6. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,057
  7. 2021Barlow Twins: Self-Supervised Learning via Redundancy Reductioncited by 1,838
  8. 2020Tabular Transformers for Modeling Multivariate Time Seriescited by 77
  9. 2020CoLES: Contrastive Learning for Event Sequences with Self-Supervisioncited by 32
  10. 2019E.T.-RNN: Applying Deep Learning to Credit Loan Applicationscited by 26
  11. 2024Learning Transactions Representations for Information Management in Banks: Mastering Local, Global, and External Knowledgecited by 6
  12. 2024Pretext Training Algorithms for Event Sequence Datacited by 1

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