20.500.12556/RUL-168462 SELLMA semantic location through on-device LLMs and WiFi sensing Understanding a user's semantic location is of critical importance in numerous areas of mobile computing, such as mobile healthcare, mobile advertising, and mobile personal assistance. Nevertheless, inferring semantic location remains challenging and often relies on translating raw geographical coordinates via third-party online services. In this paper we introduce SELLMA, an approach for semantic location inference that harnesses Wi-Fi SSID sensing and on-device querying of a specially crafted LLM. We implement SELLMA in Android and show that it can uncover a number of environmental and geographical descriptors of a users location in a privacy-preserving manner, without the need for GPS querying, and without reliance on Web-based services. mobile sensing large language models semantic location location sensing LLM fine-tuning WiFi sensing ubiquitous computing human-centered computing ubiquitous and mobile computing computer systems organization embedded and cyber-physical systems computing methodologies machine learning mobilno zaznavanje veliki jezikovni modeli opisna lokacija true false true Angleški jezik Slovenski jezik Neznano 2025-04-14 14:45:05 2025-04-14 14:45:06 2026-01-22 17:03:36 0000-00-00 00:00:00 2025 0 0 Str. 7-12 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004 10.1145/3721888.3722091 232037379 231904003 RAZ_Korelic_Martin_2025.pdf RAZ_Korelic_Martin_2025.pdf 1 3BDB583EBDF0CE99E533162667A0FD8E 5220364b93ff618ff6e0299b6823ee0517be50fa2ccd5056f4a859a382654f41 cfa6d556-192d-11f0-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=201962 https://dl.acm.org/doi/10.1145/3721888.3722091 1 2e0bac5a-192d-11f0-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=201961 Fakulteta za računalništvo in informatiko 0 0 0