Home Journals Articles Updates About
CN
image
收藏切换
Survey of Chain of Thought Techniques in Large Language Models
收藏切换
PDF
Jiale DU1, Shudong CHEN1, *, Liang YE2, Ergang WANG1, Yitong ZHAO3
Radio Communications Technology | 2025, 51(5) : 877 - 887
Less
收藏切换
Radio Communications Technology | 2025, 51(5): 877-887
• Expert Forum •
Survey of Chain of Thought Techniques in Large Language Models
Full
Jiale DU1, Shudong CHEN1, *, Liang YE2, Ergang WANG1, Yitong ZHAO3
Affiliations
  • 1.Institute of Microelectronics of the Chinese Academy of Sciences, Beijing 100029, China
  • 2.School of Emergency Management Science and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • 3.School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Published: 2025-09-18 doi: 10.3969/j.issn.1003-3114.2025.05.001
Outline
收藏切换

Driven by the ever-increasing supply of computational resources, the parameter size of Large Language Models(LLMs) continues to expand and their task performance in natural language processing has become more superior. However, there are still limitations when faced with reasoning problems, especially in common-sense reasoning or mathematical problems. Chain of Thought(CoT) significantly improves its ability to solve problems in different domains by guiding the model to generate reasoning steps. In this paper, we not only sort out the theoretical foundation system and technical evolution of CoT from the perspective of training method, but also further discuss application scenarios such as government service and enterprise digitalisation. Finally, in the light of the development trend of Artificial Intelligence (AI), the paper discusses the essential role of CoT in the development of LLMs towards a higher cognitive level from the perspective of the degree of AI, and points out the challenges and technical bottlenecks that need to be solved at the present time.

LLMs  /  CoT  /  reasoning  /  AI
Jiale DU, Shudong CHEN, Liang YE, Ergang WANG, Yitong ZHAO. Survey of Chain of Thought Techniques in Large Language Models[J]. Radio Communications Technology, 2025 , 51 (5) : 877 -887 . DOI: 10.3969/j.issn.1003-3114.2025.05.001
Appendix
Less
Year 2025 volume 51 Issue 5
PDF
147
68
Cite this Article
BibTeX
Article Info
doi: 10.3969/j.issn.1003-3114.2025.05.001
  • Receive Date：2025-04-29
  • Online Date：2026-04-17
  • Published：2025-09-18
Article Data
Affiliations
History
  • Received：2025-04-29
Affiliations
    1.Institute of Microelectronics of the Chinese Academy of Sciences, Beijing 100029, China
    2.School of Emergency Management Science and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
    3.School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
References
Share
https://castjournals.cast.org.cn/joweb/wxdtxjs/EN/10.3969/j.issn.1003-3114.2025.05.001
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House