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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.08843 |
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| _version_ | 1866908447235112960 |
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| author | Soni, Arpita Tripathi, Sahil Kashyap, Gautam Siddharth Kulahara, Manaswi Azeez, Mohammad Anas Siddiqui, Zohaib Hasan Joshi, Nipun Gao, Jiechao |
| author_facet | Soni, Arpita Tripathi, Sahil Kashyap, Gautam Siddharth Kulahara, Manaswi Azeez, Mohammad Anas Siddiqui, Zohaib Hasan Joshi, Nipun Gao, Jiechao |
| contents | We propose FLLL3M--Federated Learning with Large Language Models for Mobility Modeling--a privacy-preserving framework for Next-Location Prediction (NxLP). By retaining user data locally and leveraging LLMs through an efficient outer product mechanism, FLLL3M ensures high accuracy with low resource demands. It achieves SOT results on Gowalla (Acc@1: 12.55, MRR: 0.1422), WeePlace (10.71, 0.1285), Brightkite (10.42, 0.1169), and FourSquare (8.71, 0.1023), while reducing parameters by up to 45.6% and memory usage by 52.7%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_08843 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Can We Predict Your Next Move Without Breaking Your Privacy? Soni, Arpita Tripathi, Sahil Kashyap, Gautam Siddharth Kulahara, Manaswi Azeez, Mohammad Anas Siddiqui, Zohaib Hasan Joshi, Nipun Gao, Jiechao Machine Learning Artificial Intelligence We propose FLLL3M--Federated Learning with Large Language Models for Mobility Modeling--a privacy-preserving framework for Next-Location Prediction (NxLP). By retaining user data locally and leveraging LLMs through an efficient outer product mechanism, FLLL3M ensures high accuracy with low resource demands. It achieves SOT results on Gowalla (Acc@1: 12.55, MRR: 0.1422), WeePlace (10.71, 0.1285), Brightkite (10.42, 0.1169), and FourSquare (8.71, 0.1023), while reducing parameters by up to 45.6% and memory usage by 52.7%. |
| title | Can We Predict Your Next Move Without Breaking Your Privacy? |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2507.08843 |