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arXiv · 2504.06511

GTS-LUM: Reshaping User Behavior Modeling with LLMs in Telecommunications Industry

Liu Shi·Tianwu Zhou·Wei Xu·Li Liu·Zhexin Cui·Shaoyi Liang·Haoxing Niu·Yichong Tian·Jianwei Guo
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Abstract

As telecommunication service providers shifting their focus to analyzing user behavior for package design and marketing interventions, a critical challenge lies in developing a unified, end-to-end framework capable of modeling long-term and periodic user behavior sequences with diverse time granularities, multi-modal data inputs, and heterogeneous labels. This paper introduces GTS-LUM, a novel user behavior model that redefines modeling paradigms in telecommunication settings. GTS-LUM adopts a (multi-modal) encoder-adapter-LLM decoder architecture, enhanced with several telecom-specific innovations. Specifically, the model incorporates an advanced timestamp processing method to handle varying time granularities. It also supports multi-modal data inputs -- including structured tables and behavior co-occurrence graphs -- and aligns these with semantic information extracted by a tokenizer using a Q-former structure. Additionally, GTS-LUM integrates a front-placed target-aware mechanism to highlight historical behaviors most relevant to the target. Extensive experiments on industrial dataset validate the effectiveness of this end-to-end framework and also demonstrate that GTS-LUM outperforms LLM4Rec approaches which are popular in recommendation systems, offering an effective and generalizing solution for user behavior modeling in telecommunications.

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Liu Shi, Tianwu Zhou, Wei Xu, Li Liu, Zhexin Cui, Shaoyi Liang, Haoxing Niu, Yichong Tian, Jianwei Guo. 2025-04-09. GTS-LUM: Reshaping User Behavior Modeling with LLMs in Telecommunications Industry. https://arxiv.org/abs/2504.06511

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