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千笔AI论文

千笔AI论文

Writing & Text

Qianbi AI Paper (formerly AIPaperPass) is the first free AI paper-writing platform on the web for revision and academic writing. It can generate 50,000 words in 5 minutes, provides real online data, charts, tables, formulas, and code, offers an unlimited-use 2,000-word three-level outline, and includes PPT, proposal report, assignment brief, and 40 real references. Refund available if CNKI AIGC rate exceeds 25% or similarity rate exceeds 15%.

AI Writing ToolsAI Paper Generation
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About

Overview

Qianbi AI Paper (formerly AIPaperPass, currently displayed on the official website as “Qianbi Writing”) is an AI writing and text tool designed for paper-writing scenarios, focusing on generating paper first drafts, outline design, literature reviews, proposal reports, assignment briefs, and supporting content such as thesis defense PPTs. According to the official website, the platform supports generating longer paper content in a relatively short time and can provide common paper components such as charts, tables, formulas, code, and references.

Applicable scenarios include assisting with paper writing at the junior college, undergraduate, and graduate levels, and it can also be used for literature organization, structure building, and first-draft polishing reference. It should be noted that this type of tool is more suitable as a writing aid, and users are still advised to verify and revise the final content based on the actual research process, advisor requirements, and academic standards.

Main Features

  • Paper first-draft generation: Can generate longer first drafts of papers based on the paper topic and field of study.
  • Three-level outline generation and editing: Supports generating a three-level paper outline of about 2,000 words and allows multiple revisions.
  • Supplementing paper elements: Can provide support for common paper content such as charts, tables, formulas, code, and real online data.
  • Reference assistance: Provides about 40 references, covering both Chinese and English literature scenarios.
  • Literature review generation: Supports organizing Chinese and English literature reviews and abstract-type content.
  • Proposal reports and assignment briefs: Can generate materials needed in the early stages of paper writing, such as proposal reports and assignment briefs.
  • Thesis defense PPT generation: Provides assistance with creating thesis defense presentation PPTs.
  • Support related to reducing similarity and reducing AI traces: The official website description mentions that the platform also covers usage scenarios for reducing similarity and reducing AI traces.

Pricing

According to currently available public information, the platform offers tiered pricing, mainly including:

  • Paper first draft
    • Junior college, about 10,000 words: RMB 49.9
    • Undergraduate, about 20,000 words: RMB 49.9
    • Graduate, about 30,000 words: RMB 69.9
  • Additional services
    • Proposal report: RMB 4.9
    • Assignment brief: RMB 4.9
    • Thesis defense presentation PPT: RMB 19.9

Actual prices may vary due to version, promotions, or service adjustments. It is recommended to refer to the order page.

Frequently Asked Questions

Is there a free trial?

Yes. Public information shows that the platform offers a free paper outline generation trial. Some descriptions mention that it can generate an outline of about 3,000 words for free. Specific details are subject to the current rules on the official website.

Does the generated content include references?

Yes. The platform claims it can provide about 40 real references and supports both Chinese and English literature scenarios.

What users is it suitable for?

It is mainly suitable for assisting with paper writing for junior college, undergraduate, and graduate students, and is also suitable for users who need supporting materials such as proposal reports, literature reviews, and thesis defense PPTs.

What should be noted when using it?

AI-generated content cannot replace real academic research. When using it, users should focus on checking data sources, the authenticity of references, argument logic, formatting standards, and similarity rates, and avoid directly submitting unverified content.

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