综述专业大模型发展，揭示其在医疗金融等领域的突破
Survey of Specialized Large Language Model
- 从微调转向领域原生架构设计，提升专业性能
- 在医疗金融等领域任务上显著优于通用模型
- 适合关注垂直领域AI落地的开发者与研究者
专用大语言模型的快速发展已从简单的领域适配演进为复杂的原生架构设计，标志着人工智能发展的范式转变。本综述系统分析了医疗、金融、法律和技术等领域的进展。除广泛应用外，近期技术突破包括超越微调的领域原生设计、通过稀疏计算和量化实现参数高效、以及多模态能力的增强。这些创新有效解决了通用大模型在专业应用中的根本局限，专用模型在特定任务基准测试中表现持续领先。综述进一步指出其对电子商务领域的启示，填补该领域研究空白。
原文摘要 · Abstract (English)
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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