A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.
This survey systematically defines Small Language Models (SLMs), provides a taxonomy of methods for their acquisition, application, enhancement, and reliability, and offers frameworks for their effective use in resource-constrained settings.
Taiwo Samuel Ajani, Agbotiname Lucky Imoize, Aderemi A. Atayero
A survey of optimization techniques for implementing machine learning algorithms on resource-constrained embedded and mobile devices, covering algorithms, hardware, and applications.
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This paper presents the first comprehensive study of small language models (SLMs) for edge deployment, demystifying their capabilities and trade-offs on resource-constrained devices.
Andrés Marafioti, Orr Zohar, Miquel Farr'e, et al.
SmolVLM introduces a family of compact vision-language models achieving strong performance on resource-constrained devices through aggressive token compression and optimized encoder-LM balance.
R. Doriguzzi-Corin, S. Millar, S. Scott-Hayward, et al.
Lucid is a lightweight CNN-based DDoS detection system that matches state-of-the-art accuracy with a 40x reduction in processing time, suitable for resource-constrained environments.