"A Contemporary Overview: Trends and Applications of Large Language Models on Mobile Devices"

This paper explores deploying LLMs on mobile devices.

Discusses about personalization, privacy, and real-time processing.

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https://arxiv.org/abs/2412.03772

🤔 Original Problem:

→ Traditional cloud-based LLM deployment faces latency issues and privacy concerns

→ Mobile devices lack computational resources to run full-scale LLMs effectively

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→ Local inference using Neural Processing Units enables efficient processing without cloud dependence

→ Model compression and knowledge distillation reduce computational demands while maintaining performance

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💡 Key Insights:

→ Local processing significantly enhances data privacy and security

→ Offline capability ensures consistent performance without network dependency

→ Hardware advancements like NPUs make efficient local inference possible