Guangzhou University
"Research Paper Analyst" AI Agent
Release date:2025.07.24
Pain points of demand
Review efficiency bottleneck: Each paper must be read individually, which is time-consuming and labor-intensive. This becomes especially challenging when dealing with a large volume of papers, as it’s difficult to balance efficiency with quality. Moreover, repetitive tasks—such as format checks and basic logic verification—continue to account for a disproportionately high percentage of the workload.
Challenges in Quality Control: Student papers commonly suffer from issues such as missing literature reviews, insufficiently robust methodological justification, and overly vague conclusions. When it comes to assessing originality, reliance largely depends on teachers' subjective experience, with a notable lack of objective criteria to provide solid support—making it urgently necessary to develop relevant tools that can offer much-needed assistance.

Solution
Providing a review assistant for paper reading
Private deployment of large models, enabling 100% autonomous data management.
Supports fully automated plagiarism detection and format checking, backed by AI-powered multi-dimensional intelligent assessment system.
Achieving the integration of AI intelligence with educational informatization
Private knowledge base construction provides teachers with multi-dimensional evaluation criteria for paper review.
Impact Value
High-performance support
Data Security Assurance
Value Extension
Increased efficiency
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