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arXiv · 2508.19667

Survey of Specialized Large Language Model

Chenghan Yang·Ruiyu Zhao·Yang Liu·Ling Jiang
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Abstract

The rapid evolution of specialized large language models (LLMs) has transitioned from simple domain adaptation to sophisticated native architectures, marking a paradigm shift in AI development. This survey systematically examines this progression across healthcare, finance, legal, and technical domains. Besides the wide use of specialized LLMs, technical breakthrough such as the emergence of domain-native designs beyond fine-tuning, growing emphasis on parameter efficiency through sparse computation and quantization, increasing integration of multimodal capabilities and so on are applied to recent LLM agent. Our analysis reveals how these innovations address fundamental limitations of general-purpose LLMs in professional applications, with specialized models consistently performance gains on domain-specific benchmarks. The survey further highlights the implications for E-Commerce field to fill gaps in the field.

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Chenghan Yang, Ruiyu Zhao, Yang Liu, Ling Jiang. 2025-08-27. Survey of Specialized Large Language Model. https://arxiv.org/abs/2508.19667

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