From Machine Learning-Based to LLM-Enhanced: An Application-Focused Analysis of How Social IoT Benefits from LLMs
Recent advancements in large language models (LLMs) have added a transformative dimension to the social Internet of Things (SIoT), which is the combination of social networks and IoT. With LLMs’ natural language understanding and data synthesis capabilities, LLMs are regarded as strong tools to enha...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
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| Series: | IoT |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-831X/6/2/26 |
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| Summary: | Recent advancements in large language models (LLMs) have added a transformative dimension to the social Internet of Things (SIoT), which is the combination of social networks and IoT. With LLMs’ natural language understanding and data synthesis capabilities, LLMs are regarded as strong tools to enhance SIoT applications such as recommendation, search, and data management. This application-focused review synthesizes the latest related research by identifying both the synergies and the current research gaps at the intersection of LLMs and SIoT, as well as the evolutionary road from machine learning-based solutions to LLM-enhanced ones. |
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| ISSN: | 2624-831X |