
睿信论文检测
Writing & TextRuixin Paper AI Detection is a one-stop academic integrity detection system launched by CAS Ruijian, focusing on AIGC (AI-generated content) detection and academic misconduct identification.
About
Overview
Ruixin Paper Detection is an academic integrity detection platform launched by CAS Ruijian, positioned for AIGC detection and academic misconduct risk identification in papers and academic content. The product is aimed at university teachers and students, supervisors, and institutional administrative departments, and supports comprehensive analysis of paper text as well as academic images, helping users complete self-checks before submission.
The platform's distinguishing feature is that it covers both AI-generated text detection and academic image authenticity verification at the same time. In addition to common paper paragraphs, it can also detect traces of AI generation or tampering risks in experimental images, data charts, statistical graphics, and other content, and outputs reports with risk levels, suspected paragraph locations, and revision suggestions for further verification and revision.
Main Features
- AI text detection: Identifies content in papers that is suspected to have been generated by models such as ChatGPT, ERNIE Bot, Doubao, and DeepSeek, and marks high-risk paragraphs.
- Academic image detection: Supports identification of AI-generated traces and tampering detection for academic images such as experimental images, data charts, and statistical graphics.
- Comprehensive detection reports: Provides overall AI risk results, risk grading, paragraph-level highlighted positioning, and revision suggestions to enhance result interpretability.
- Batch detection processing: The teacher side can batch upload undergraduate, master's, and doctoral theses as well as course assignments, improving centralized review efficiency.
- Multi-format compatibility: Supports common formats such as DOCX, PDF, and JPG, suitable for mixed text-and-image documents.
- Management backend: Institutional administrators can view multidimensional statistical analysis data to understand the overall academic integrity situation.
- Cross-device interoperability: Supports account interoperability between the PC side and the "Ruijian AI" WeChat Mini Program, making it convenient to check detection progress and reports at any time.
- Data security protection: Provides encrypted transmission and storage, and supports mechanisms such as private deployment and scheduled destruction of original papers.
Product Pricing
At present, no clear unified pricing description has been found in publicly available information. According to the product introduction, the platform may provide differentiated plans for different roles and institutions, including the teacher side, institutional management side, API integration, private deployment, and more. For specific prices, detection counts, and purchasing methods, please refer to the official website or official business consultation.
Frequently Asked Questions
Who is Ruixin Paper Detection suitable for?
It is suitable for undergraduate, master's, and doctoral students to conduct paper self-checks, and is also suitable for supervisors, course instructors, journal submission authors, and institutional academic affairs management departments.
What content can be detected?
In addition to the main text of papers, it can also detect academic image content such as experimental images, data charts, and statistical graphics, making it suitable for the review of multimodal academic materials.
Which file formats are supported?
The publicly supported formats include DOCX, PDF, JPG, among others, and it can process common paper and image materials.
What does the detection result include?
It usually includes overall AI risk results, risk levels, suspected paragraph highlighting, image risk alerts, and corresponding revision suggestions, making it convenient for users to conduct further manual review.
Does it support batch detection and institutional deployment?
It supports batch upload and batch detection on the teacher side, while also providing institution-level usage methods such as private deployment and API integration.
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