Multi-perspective consistency checking for large language model hallucination detection: a black-box zero-resource approach

Linggang KONG; Xiaofeng ZHONG; Jie CHEN; Haoran FU; Yongjie WANG

doi:10.1631/FITEE.2500180

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Multi-perspective consistency checking for large language model hallucination detection: a black-box zero-resource approach

Regular Papers | Updated：2026-01-07

- Multi-perspective consistency checking for large language model hallucination detection: a black-box zero-resource approach
- 多视角一致性校验的大语言模型幻觉检测：一种黑盒零资源方法
- “Reporting on the latest advancements in the field of artificial intelligence, researchers have developed a black-box zero-resource approach for detecting hallucinations in large language models. This innovative method leverages multi-perspective consistency checking, significantly improving the detection of erroneous content without relying on external resources.”
- Frontiers of Information Technology & Electronic Engineering Vol. 26, Issue 11, Pages: 2298-2309(2025)
- Affiliations：
  
  1.College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China
  2.Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation, Hefei 230037, China
- Author bio：
  
  E-mail: konglinggang@nudt.edu.cn
  ‡ Corresponding author
- Funds：
- DOI：10.1631/FITEE.2500180
  CLC： TP18
- Received：21 March 2025，
  
  Revised：2025-10-08，
  
  Published Online：24 November 2025，
  
  Published：2025-11
- Accepted：
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Linggang KONG, Xiaofeng ZHONG, Jie CHEN, et al. Multi-perspective consistency checking for large language model hallucination detection: a black-box zero-resource approach[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(11): 2298-2309.
DOI：

Linggang KONG, Xiaofeng ZHONG, Jie CHEN, et al. Multi-perspective consistency checking for large language model hallucination detection: a black-box zero-resource approach[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(11): 2298-2309. DOI： 10.1631/FITEE.2500180.

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Multi-perspective consistency checking for large language model hallucination detection: a black-box zero-resource approach

DOI：10.1631/FITEE.2500180