Author(s)

Jing Xie ¹, Shilong Li ¹, Chuan Huang ¹, Xiangjun Kong ¹, Yongjie Zhu ¹

Affiliation(s)

¹ State Grid Shanghai Electric Power Company Shinan District Power Supply Company, Shanghai, China

Corresponding Author

Jing Xie

ABSTRACT

Manual review of complex State Grid documentation suffers from inefficiency and oversight limitations. To address these issues, this research proposes an intelligent agent framework based on the Brightness Large Model for automated verification. The methodology integrates three core components. First, a shared semantic space fuses text, table, and diagram data to enable deep understanding and structured summarization. Second, a Retrieval-Augmented Generation system maintains a dynamic knowledge base to ensure strict alignment with evolving regulations. Third, a multi-agent pipeline facilitates collaborative rule matching, inconsistency detection, and automated revision. This system provides robust risk warnings and decision support, optimizing resource allocation while advancing smart grid development and national energy security.

KEYWORDS

Multimodal Reasoning, Intelligent Agent, Smart Grid Management

CITE THIS PAPER

Jing Xie, Shilong Li, Chuan Huang, Xiangjun Kong, Yongjie Zhu, Research on Multimodal Reasoning and Self-Verifying Agents Based on the Brightness Large Model for Report Materials. Advances in Computer, Signals and Systems (2025) Vol. 9: 83-90. DOI: http://dx.doi.org/10.23977/acss.2025.090410.

REFERENCES

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